Configuration

NAIAD with Uniform acquisition

NAIAD ensemble retrained each round, with the next pairs chosen by Uniform acquisition.

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Evaluations and results

4 evaluations · 21 results. Different protocols are not a single leaderboard.

Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4

Sorted by True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 4 of active learning) (higher is better). The best value in each column is highlighted. Decimals are rounded for display; each value links to the printed value and its source.

Tested configuration	Protocol and dataset	True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 4 of active learning)	Count (marginal gain (P_4 - P_0)/4 in the screen's 200 strongest measured gene pairs found, round 0 to round 4)	True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 0 of active learning)	True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 1 of active learning)	True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 2 of active learning)	True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 3 of active learning)
NAIAD with Uniform acquisitionEvaluation	Norman et al. 2019 combinatorial CRISPRa in K562, gene-level viability (as processed by Qin et al. 2025)	93.7 (0.7) (best in column)	Not reported	86.0 (1.0)	88.3 (2.0)	88.3 (0.3)	89.7 (1.2)
NAIAD with Uniform acquisitionEvaluation	Norman et al. 2019 combinatorial CRISPRa in K562, gene-level viability (as processed by Qin et al. 2025)	93.3 (0.7)	Not reported	Not reported	Not reported	Not reported	Not reported
NAIAD with Uniform acquisitionEvaluation	Norman et al. 2019 combinatorial CRISPRa in K562, gene-level viability (as processed by Qin et al. 2025)	93.3 (2.9)	Not reported	Not reported	Not reported	Not reported	Not reported
NAIAD with Uniform acquisitionEvaluation	Norman et al. 2019 combinatorial CRISPRa in K562, gene-level viability (as processed by Qin et al. 2025)	92	1	Not reported	Not reported	Not reported	Not reported
NAIAD with Uniform acquisitionEvaluation	Horlbeck et al. 2018 combinatorial CRISPRi in Jurkat T cells, gene-level viability (as processed by Qin et al. 2025)	81.3 (0.9)	Not reported	Not reported	Not reported	Not reported	Not reported
NAIAD with Uniform acquisitionEvaluation	Horlbeck et al. 2018 combinatorial CRISPRi in Jurkat T cells, gene-level viability (as processed by Qin et al. 2025)	80.3 (0.3)	Not reported	Not reported	Not reported	Not reported	Not reported
NAIAD with Uniform acquisitionEvaluation	Horlbeck et al. 2018 combinatorial CRISPRi in Jurkat T cells, gene-level viability (as processed by Qin et al. 2025)	79	2.5	Not reported	Not reported	Not reported	Not reported
NAIAD with Uniform acquisitionEvaluation	Simpson et al. 2023 combinatorial CRISPRi in K562, gene-level viability (as processed by Qin et al. 2025)	70.3 (5.0)	Not reported	Not reported	Not reported	Not reported	Not reported
NAIAD with Uniform acquisitionEvaluation	Simpson et al. 2023 combinatorial CRISPRi in K562, gene-level viability (as processed by Qin et al. 2025)	69.0 (1.1)	Not reported	Not reported	Not reported	Not reported	Not reported
NAIAD with Uniform acquisitionEvaluation	Simpson et al. 2023 combinatorial CRISPRi in K562, gene-level viability (as processed by Qin et al. 2025)	66	7.5 (best in column)	Not reported	Not reported	Not reported	Not reported
NAIAD with Uniform acquisitionEvaluation	Horlbeck et al. 2018 combinatorial CRISPRi in K562, gene-level viability (as processed by Qin et al. 2025)	39	0.5	Not reported	Not reported	Not reported	Not reported
NAIAD with Uniform acquisitionEvaluation	Horlbeck et al. 2018 combinatorial CRISPRi in K562, gene-level viability (as processed by Qin et al. 2025)	39.0 (0.6)	Not reported	Not reported	Not reported	Not reported	Not reported
NAIAD with Uniform acquisitionEvaluation	Horlbeck et al. 2018 combinatorial CRISPRi in K562, gene-level viability (as processed by Qin et al. 2025)	38.7 (0.3)	Not reported	Not reported	Not reported	Not reported	Not reported

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Horlbeck et al. 2018 combinatorial CRISPRi in Jurkat T cells, gene-level viability (as processed by Qin et al. 2025)	2.5 Count (marginal gain (P_4 - P_0)/4 in the screen's 200 strongest measured gene pairs found, round 0 to round 4) count · higher Uncertainty: Not reported by the source: The table prints no error and does not state the number of runs. Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Horlbeck Jurkat (Tables 2 and 3, acquisition functions with NAIAD) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 3, row "Uniform", column "Horlbeck Jurkat"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Horlbeck et al. 2018 combinatorial CRISPRi in Jurkat T cells, gene-level viability (as processed by Qin et al. 2025)	79 True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 4 of active learning) count · higher Uncertainty: Not reported by the source: The table prints no error and does not state the number of runs. Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Horlbeck Jurkat (Tables 2 and 3, acquisition functions with NAIAD) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 2, row "Uniform", column "Horlbeck Jurkat"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Horlbeck et al. 2018 combinatorial CRISPRi in K562, gene-level viability (as processed by Qin et al. 2025)	0.5 Count (marginal gain (P_4 - P_0)/4 in the screen's 200 strongest measured gene pairs found, round 0 to round 4) count · higher Uncertainty: Not reported by the source: The table prints no error and does not state the number of runs. Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Horlbeck K562 (Tables 2 and 3, acquisition functions with NAIAD) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 3, row "Uniform", column "Horlbeck K562"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Horlbeck et al. 2018 combinatorial CRISPRi in K562, gene-level viability (as processed by Qin et al. 2025)	39 True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 4 of active learning) count · higher Uncertainty: Not reported by the source: The table prints no error and does not state the number of runs. Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Horlbeck K562 (Tables 2 and 3, acquisition functions with NAIAD) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 2, row "Uniform", column "Horlbeck K562"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Norman et al. 2019 combinatorial CRISPRa in K562, gene-level viability (as processed by Qin et al. 2025)	1 Count (marginal gain (P_4 - P_0)/4 in the screen's 200 strongest measured gene pairs found, round 0 to round 4) count · higher Uncertainty: Not reported by the source: The table prints no error and does not state the number of runs. Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Norman (Tables 2 and 3, acquisition functions with NAIAD) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 3, row "Uniform", column "Norman"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Norman et al. 2019 combinatorial CRISPRa in K562, gene-level viability (as processed by Qin et al. 2025)	92 True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 4 of active learning) count · higher Uncertainty: Not reported by the source: The table prints no error and does not state the number of runs. Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Norman (Tables 2 and 3, acquisition functions with NAIAD) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 2, row "Uniform", column "Norman"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Simpson et al. 2023 combinatorial CRISPRi in K562, gene-level viability (as processed by Qin et al. 2025)	7.5 Count (marginal gain (P_4 - P_0)/4 in the screen's 200 strongest measured gene pairs found, round 0 to round 4) count · higher Uncertainty: Not reported by the source: The table prints no error and does not state the number of runs. Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Simpson (Tables 2 and 3, acquisition functions with NAIAD) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 3, row "Uniform", column "Simpson"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Simpson et al. 2023 combinatorial CRISPRi in K562, gene-level viability (as processed by Qin et al. 2025)	66 True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 4 of active learning) count · higher Uncertainty: Not reported by the source: The table prints no error and does not state the number of runs. Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Simpson (Tables 2 and 3, acquisition functions with NAIAD) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 2, row "Uniform", column "Simpson"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Horlbeck et al. 2018 combinatorial CRISPRi in Jurkat T cells, gene-level viability (as processed by Qin et al. 2025)	81.3 (0.9) True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 4 of active learning) count · higher Uncertainty: SE 0.9. Caption: error is SE across three cross-fold replicates Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Horlbeck Jurkat (Table 4, NAIAD against RECOVER by acquisition function) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 4, row "NAIAD Uniform", column "Horlbeck Jurkat"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Horlbeck et al. 2018 combinatorial CRISPRi in K562, gene-level viability (as processed by Qin et al. 2025)	38.7 (0.3) True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 4 of active learning) count · higher Uncertainty: SE 0.3. Caption: error is SE across three cross-fold replicates Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Horlbeck K562 (Table 4, NAIAD against RECOVER by acquisition function) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 4, row "NAIAD Uniform", column "Horlbeck K562"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Norman et al. 2019 combinatorial CRISPRa in K562, gene-level viability (as processed by Qin et al. 2025)	93.3 (0.7) True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 4 of active learning) count · higher Uncertainty: SE 0.7. Caption: error is SE across three cross-fold replicates Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Norman (Table 4, NAIAD against RECOVER by acquisition function) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 4, row "NAIAD Uniform", column "Norman"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Simpson et al. 2023 combinatorial CRISPRi in K562, gene-level viability (as processed by Qin et al. 2025)	70.3 (5.0) True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 4 of active learning) count · higher Uncertainty: SE 5.0. Caption: error is SE across three cross-fold replicates Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Simpson (Table 4, NAIAD against RECOVER by acquisition function) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 4, row "NAIAD Uniform", column "Simpson"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Norman et al. 2019 combinatorial CRISPRa in K562, gene-level viability (as processed by Qin et al. 2025)	86.0 (1.0) True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 0 of active learning) count · higher Uncertainty: SE 1.0. Caption: error is SE across three cross-fold replicates Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Norman (Table 7, NAIAD, RECOVER and GEARS over rounds on Norman) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 7, row "NAIAD Uniform", column "Round 0"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Norman et al. 2019 combinatorial CRISPRa in K562, gene-level viability (as processed by Qin et al. 2025)	88.3 (2.0) True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 1 of active learning) count · higher Uncertainty: SE 2.0. Caption: error is SE across three cross-fold replicates Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Norman (Table 7, NAIAD, RECOVER and GEARS over rounds on Norman) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 7, row "NAIAD Uniform", column "Round 1"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Norman et al. 2019 combinatorial CRISPRa in K562, gene-level viability (as processed by Qin et al. 2025)	88.3 (0.3) True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 2 of active learning) count · higher Uncertainty: SE 0.3. Caption: error is SE across three cross-fold replicates Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Norman (Table 7, NAIAD, RECOVER and GEARS over rounds on Norman) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 7, row "NAIAD Uniform", column "Round 2"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Norman et al. 2019 combinatorial CRISPRa in K562, gene-level viability (as processed by Qin et al. 2025)	89.7 (1.2) True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 3 of active learning) count · higher Uncertainty: SE 1.2. Caption: error is SE across three cross-fold replicates Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Norman (Table 7, NAIAD, RECOVER and GEARS over rounds on Norman) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 7, row "NAIAD Uniform", column "Round 3"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Norman et al. 2019 combinatorial CRISPRa in K562, gene-level viability (as processed by Qin et al. 2025)	93.7 (0.7) True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 4 of active learning) count · higher Uncertainty: SE 0.7. Caption: error is SE across three cross-fold replicates Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Norman (Table 7, NAIAD, RECOVER and GEARS over rounds on Norman) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 7, row "NAIAD Uniform", column "Round 4"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Horlbeck et al. 2018 combinatorial CRISPRi in Jurkat T cells, gene-level viability (as processed by Qin et al. 2025)	80.3 (0.3) True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 4 of active learning) count · higher Uncertainty: SE 0.3. Caption: error is SE across three cross-fold replicates Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Horlbeck Jurkat (Table 8, Mean-UCB beta with NAIAD) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 8, row "Uniform", column "Horlbeck Jurkat"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Horlbeck et al. 2018 combinatorial CRISPRi in K562, gene-level viability (as processed by Qin et al. 2025)	39.0 (0.6) True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 4 of active learning) count · higher Uncertainty: SE 0.6. Caption: error is SE across three cross-fold replicates Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Horlbeck K562 (Table 8, Mean-UCB beta with NAIAD) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 8, row "Uniform", column "Horlbeck K562"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Norman et al. 2019 combinatorial CRISPRa in K562, gene-level viability (as processed by Qin et al. 2025)	93.3 (2.9) True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 4 of active learning) count · higher Uncertainty: SE 2.9. Caption: error is SE across three cross-fold replicates Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Norman (Table 8, Mean-UCB beta with NAIAD) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 8, row "Uniform", column "Norman"
Configuration: NAIAD with Uniform acquisition	Protocol: Retrospective active learning on a fully measured two-gene CRISPR viability screen: top-200 gene pairs found by round 4 Dataset: Simpson et al. 2023 combinatorial CRISPRi in K562, gene-level viability (as processed by Qin et al. 2025)	69.0 (1.1) True positives (the screen's 200 strongest measured gene pairs found among the 200 strongest measured-plus-predicted values, round 4 of active learning) count · higher Uncertainty: SE 1.1. Caption: error is SE across three cross-fold replicates Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source NAIAD with Uniform acquisition on Simpson (Table 8, Mean-UCB beta with NAIAD) pheno-20261022-qin2025-protocol-al-top200 Aggregation: Not reported Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Table 8, row "Uniform", column "Simpson"

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Qin et al. 2025, Active Learning for Efficient Discovery of Optimal Combinatorial Perturbations (ICML 2025, PMLR 267) · Original source · Proceedings of the 42nd ICML, PMLR 267:50363-50383, 2025; proceedings PDF qin25g.pdf. The arXiv preprint 2411.12010 was not read.

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Stable ID: pheno-20261022-qin2025-config-naiad-uniform

areas: cells-tissues
contexts: research
method types: supervised_machine_learning
reported name: NAIAD, Uniform
configuration type: paper_evaluation
foundation model eligible: false
version: As run by Qin et al. 2025 (PMLR 267); no release or commit is printed
access reuse: NAIAD code at https://github.com/NeptuneBio/NAIAD (Apache-2.0 per GitHub metadata); the commit used for the paper is not stated
parameters: NAIAD ensemble with adaptive gene-embedding size (Table 9 schedule), retrained each round; seed set of uniformly sampled pairs shared by all acquisition functions. Ensemble size not stated.
source locator: Tables 2 to 4 row labels; Section 5.3; Appendix C
provenance note: The paper's own method.
review: method: source-hash-verification; scope-review; reviewer: claude; reviewer note: Claude (Opus 5.5) review agent, independent of the extraction agent; no human review claimed; date: 2026-10-22; artifact sha256: 983b2da8aed78f0aced27053301c15f0f67ebd0fac706435bb6800e309dd64eb; retrieval url: https://raw.githubusercontent.com/mlresearch/v267/main/assets/qin25g/qin25g.pdf; method note: Re-hashed the PDF in the scratchpad (SHA-256 matches the source record). Read the cited sections in the pdftotext layer of the pinned PDF.; note: Fields checked against the cited locator; nothing found that the source does not state.
selection: Uniform acquisition: pairs added each round are sampled uniformly (Mean-UCB with alpha = beta = 0, Appendix C.5)

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