Protocol

CASF-2016 ranking (Protein–ligand binding affinity scoring)

CASF-2016 ranking · Spearman correlation. Training uses 3,772 PDBbind-2016 refined-set complexes after removal of the 285-complex core test set. CASF separates scoring, ranking and docking power.

Sources

AK-Score: Accurate Protein-Ligand Binding Affinity Prediction Using an Ensemble of 3D-Convolutional Neural Networks · A comparison of prediction accuracy with the CASF-2016 dataset.; Table 2 (ijms-21-08424-t002), row 3 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 4 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 5 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 6 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 7 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 8 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 9 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 10 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 11 AK-score-ensemble, column 4: CASF-2016 ranking Spearman correlation

9 evaluations · 27 results

Overview

Key specifications have not been extracted for this record. See the linked evaluation and sources for the reported setup.

limited source coverage · Automated source review, 2026-09-17. All specifications and missing details

Results

Each comparison retains its reviewed evaluation scope, dataset and metric. Results are shown without a pooled ranking.

Evaluation scope and datasetMetric and reported setup

CASF-2016 ranking · Spearman correlation

Spearman correlation (unitless) · Higher values are better.

CASF-2016 ranking (Protein–ligand binding affinity scoring) · CASF-2016 ranking

Evidence origin: Independent external evaluation, Author-reported evaluation.

Learning rates define distinct evaluated configurations. Table 2 ensemble Pearson 0.812 is distinct from the 30-network ensemble Pearson 0.827 in Figure 3. Do not transfer the 285-complex scoring denominator to ranking or docking rows without their appropriate grouping. Origins are labelled per method; appearance in one table does not constitute independent replication of every model.

Comparison details and limitations

Training uses 3,772 PDBbind-2016 refined-set complexes after removal of the 285-complex core test set. CASF separates scoring, ranking and docking power.

Automated source review: 2026-09-17. Numerical source review does not establish independent reproduction.

Dots show point estimates. Whiskers show only explicitly defined uncertainty (standard deviation, standard error or a labelled interval); their definitions remain in Table. Unresolved uncertainty is not plotted. Differences do not establish statistical significance.

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Tested configuration

-1-0.500.51

Reported score

Methods and evaluation design

Procedure, tasks and evaluated configurations

How it works

Evaluation in this paper

Training uses 3,772 PDBbind-2016 refined-set complexes after removal of the 285-complex core test set. CASF separates scoring, ranking and docking power.

Sources

Evaluation design

Benchmarks bring together tasks and protocols. A task describes the biological question; a protocol defines a particular test.

Tasks

Protein–ligand binding affinity scoring

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Recorded evaluations

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Baseline coverage

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Null control

Proposed control: requires review

Protocol-specific valid geometric or structural control

Protocol-specific applicability, permitted inputs, access, split, evaluator and execution requirements need review before implementation or execution.

This is a suggested selection rule, not a validated method or a measured score.

Conventional reference

Proposed control: requires review

Upstream conventional structural reference with matched templates and cutoffs

Protocol-specific applicability, permitted inputs, access, split, evaluator and execution requirements need review before implementation or execution.

This is a suggested selection rule, not a validated method or a measured score.

Protocol coverage CSV · Model evaluation matrix · Source table · Release and checksums

Coverage is derived from release 2026-09-29-06401fd5b220. Source citations describe the original records; they do not validate an unreviewed baseline proposal. No results have been generated by this audit.

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Strengths, limitations and unresolved questions

Strengths and limitations

Strengths and considerations

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Limitations and conditions

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Profile review details

Primary-source transcription and separate automated review. No human sign-off or experimental reproduction.

Stable record: paper-protocol-0c5a1c5ef6896a2d96

Specifications

Inputs, training, access and other details

Explanatory profile: limited source coverage · Automated source review, 2026-09-17. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.

Data, procedure and scoring
Property	Description and evidence
Datasets	Not extracted or verified for this record.
Organisms	Not extracted or verified for this record.
Assays	Not extracted or verified for this record.
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Evidence

Source checking verifies the cited claim or transcription. It does not establish independent reproduction.

Papers and result coverage

Last literature check: 2026-09-17. Dated primary-source discovery and protocol/table screening. Source checking does not mean experimental reproduction. Only separately extracted and independently reviewed numeric batches are publishable.

Paper or primary resource	Version	Reference
AK-Score: Accurate Protein-Ligand Binding Affinity Prediction Using an Ensemble of 3D-Convolutional Neural Networks	version of record	Read source DOI: 10.3390/ijms21228424

Historical gaps recorded on 2026-09-17

The catalogue now holds 27 result rows for this benchmark. A note below about pending extraction describes the state on 2026-09-17 and may since have been answered by a later batch. The result rows and their sources are the current record.

exact checkpoint hashes and per-method scored denominators: Table labels alone do not establish these fields; do not infer checkpoint or scored count from model name or dataset size.

Search and extraction details

complete tables extracted

Searches

AK-Score: Accurate Protein-Ligand Binding Affinity Prediction Using an Ensemble of 3D-Convolutional Neural Networks 10.3390/ijms21228424

Evidence locations

A comparison of prediction accuracy with the CASF-2016 dataset.; Table 2 (ijms-21-08424-t002), row 3 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 4 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 5 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 6 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 7 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 8 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 9 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 10 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 11 AK-score-ensemble, column 4: CASF-2016 ranking Spearman correlation

Evidence table

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One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.

3 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-09-29-06401fd5b220
Property and statement	Original source and location	Review and provenance
Evaluation in this paper Training uses 3,772 PDBbind-2016 refined-set complexes after removal of the 285-complex core test set. CASF separates scoring, ranking and docking power. Individual claims	AK-Score: Accurate Protein-Ligand Binding Affinity Prediction Using an Ensemble of 3D-Convolutional Neural Networks Original source ↗ A comparison of prediction accuracy with the CASF-2016 dataset.; Table 2 (ijms-21-08424-t002), row 3 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 4 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 5 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 6 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 7 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 8 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 9 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 10 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 11 AK-score-ensemble, column 4: CASF-2016 ranking Spearman correlation Version: version of record Retrieved: 2026-09-16T10:44:03.436853+00:00	source checked automated source review · 2026-09-17 Audit details Primary-source transcription and separate automated review. No human sign-off or experimental reproduction. Field: `attributes.profile.sections.0.body` Source artifact SHA-256: `40cfd28dcd587599768ec99a6590ec593486475ff01c7b1d1f229b44aa91bf8d` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Introduction CASF-2016 ranking · Spearman correlation. Training uses 3,772 PDBbind-2016 refined-set complexes after removal of the 285-complex core test set. CASF separates scoring, ranking and docking power. Individual claims	AK-Score: Accurate Protein-Ligand Binding Affinity Prediction Using an Ensemble of 3D-Convolutional Neural Networks Original source ↗ A comparison of prediction accuracy with the CASF-2016 dataset.; Table 2 (ijms-21-08424-t002), row 3 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 4 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 5 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 6 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 7 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 8 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 9 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 10 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 11 AK-score-ensemble, column 4: CASF-2016 ranking Spearman correlation Version: version of record Retrieved: 2026-09-16T10:44:03.436853+00:00	source checked automated source review · 2026-09-17 Audit details Primary-source transcription and separate automated review. No human sign-off or experimental reproduction. Field: `attributes.profile.summary` Source artifact SHA-256: `40cfd28dcd587599768ec99a6590ec593486475ff01c7b1d1f229b44aa91bf8d` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Relationship: evaluates task reported-task-a78312d5df6dad Individual claims	AK-Score: Accurate Protein-Ligand Binding Affinity Prediction Using an Ensemble of 3D-Convolutional Neural Networks Original source ↗ A comparison of prediction accuracy with the CASF-2016 dataset.; Table 2 (ijms-21-08424-t002), row 3 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 4 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 5 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 6 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 7 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 8 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 9 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 10 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 11 AK-score-ensemble, column 4: CASF-2016 ranking Spearman correlation Version: version of record Retrieved: 2026-09-16T10:44:03.436853+00:00	source checked automated source review · 2026-09-17 Audit details Field: `links:evaluates_task:reported-task-a78312d5df6dad` Claim: paper-claim-44afb78999a73a20ae Source artifact SHA-256: `40cfd28dcd587599768ec99a6590ec593486475ff01c7b1d1f229b44aa91bf8d` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact

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AK-Score: Accurate Protein-Ligand Binding Affinity Prediction Using an Ensemble of 3D-Convolutional Neural Networks · Original source · version of record

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Technical metadata and extraction receipts

Stable ID: paper-protocol-0c5a1c5ef6896a2d96

areas: molecular-interactions
tasks: Protein–ligand binding affinity scoring
entity level: protocol
protocol: Training uses 3,772 PDBbind-2016 refined-set complexes after removal of the 285-complex core test set. CASF separates scoring, ranking and docking power.
comparison panels: id: akscore-2020-ijms-21-08424-t002-spearman; title: CASF-2016 ranking · Spearman correlation; protocol id: paper-protocol-0c5a1c5ef6896a2d96; dataset id: paper-dataset-1586129df956852448; metric: Spearman correlation; unit: unitless; direction: higher; result ids: paper-result-afde916d0d344fa5f3; paper-result-ed6bcd67134333f58a; paper-result-ebaae58e746eec83a7; paper-result-b2042668888da9601a; paper-result-ce979d714ded7834b1; paper-result-fcef1022a440b405a6; paper-result-85878ef679c27f7b5c; paper-result-e0b7d3b3917b02dad0; paper-result-7ea147a4415e34f1f0; source ids: akscore-2020; source locator: A comparison of prediction accuracy with the CASF-2016 dataset.; Table 2 (ijms-21-08424-t002), row 3 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 4 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 5 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 6 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 7 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 8 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 9 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 10 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 11 AK-score-ensemble, column 4: CASF-2016 ranking Spearman correlation; context: Training uses 3,772 PDBbind-2016 refined-set complexes after removal of the 285-complex core test set. CASF separates scoring, ranking and docking power.; caveats: Learning rates define distinct evaluated configurations. Table 2 ensemble Pearson 0.812 is distinct from the 30-network ensemble Pearson 0.827 in Figure 3. Do not transfer the 285-complex scoring denominator to ranking or docking rows without their appropriate grouping. Origins are labelled per method; appearance in one table does not constitute independent replication of every model.; review: method: automated_source_review; date: 2026-09-17; id: akscore-2020-ijms-21-08424-t002-kendall; title: CASF-2016 ranking · Kendall tau; protocol id: paper-protocol-0c5a1c5ef6896a2d96; dataset id: paper-dataset-1586129df956852448; metric: Kendall tau; unit: unitless; direction: higher; result ids: paper-result-7efbb2fd6cff6823e3; paper-result-6a2d74d436874496a7; paper-result-a1a3952f6bd9e2b283; paper-result-bb8ec19b9079636bfc; paper-result-c259bffd41e1648664; paper-result-5505231aa7e1d37837; paper-result-955fc84c22143025f1; paper-result-2eed37f01d919cd0e6; paper-result-38d90f85618bbf9bbb; source ids: akscore-2020; source locator: A comparison of prediction accuracy with the CASF-2016 dataset.; Table 2 (ijms-21-08424-t002), row 3 K DEEP, column 5: CASF-2016 ranking Kendall tau; Table 2 (ijms-21-08424-t002), row 4 K DEEP, column 5: CASF-2016 ranking Kendall tau; Table 2 (ijms-21-08424-t002), row 5 K DEEP, column 5: CASF-2016 ranking Kendall tau; Table 2 (ijms-21-08424-t002), row 6 K DEEP, column 5: CASF-2016 ranking Kendall tau; Table 2 (ijms-21-08424-t002), row 7 AK-score-single, column 5: CASF-2016 ranking Kendall tau; Table 2 (ijms-21-08424-t002), row 8 AK-score-single, column 5: CASF-2016 ranking Kendall tau; Table 2 (ijms-21-08424-t002), row 9 AK-score-single, column 5: CASF-2016 ranking Kendall tau; Table 2 (ijms-21-08424-t002), row 10 AK-score-single, column 5: CASF-2016 ranking Kendall tau; Table 2 (ijms-21-08424-t002), row 11 AK-score-ensemble, column 5: CASF-2016 ranking Kendall tau; context: Training uses 3,772 PDBbind-2016 refined-set complexes after removal of the 285-complex core test set. CASF separates scoring, ranking and docking power.; caveats: Learning rates define distinct evaluated configurations. Table 2 ensemble Pearson 0.812 is distinct from the 30-network ensemble Pearson 0.827 in Figure 3. Do not transfer the 285-complex scoring denominator to ranking or docking rows without their appropriate grouping. Origins are labelled per method; appearance in one table does not constitute independent replication of every model.; review: method: automated_source_review; date: 2026-09-17; id: akscore-2020-ijms-21-08424-t002-pi; title: CASF-2016 ranking · Predictive Index; protocol id: paper-protocol-0c5a1c5ef6896a2d96; dataset id: paper-dataset-1586129df956852448; metric: Predictive Index; unit: unitless; direction: higher; result ids: paper-result-5bc9b7cb53278a9249; paper-result-b1bed56b343f3c834f; paper-result-38ac6df2e198d58359; paper-result-5a60e66ec1c7bcaf4c; paper-result-e05720b0b94095d5af; paper-result-85c6bc19be77938986; paper-result-3d0c6443af15768910; paper-result-35759619206bf32ae8; paper-result-0d44e20dd3c089c7f3; source ids: akscore-2020; source locator: A comparison of prediction accuracy with the CASF-2016 dataset.; Table 2 (ijms-21-08424-t002), row 3 K DEEP, column 6: CASF-2016 ranking Predictive Index; Table 2 (ijms-21-08424-t002), row 4 K DEEP, column 6: CASF-2016 ranking Predictive Index; Table 2 (ijms-21-08424-t002), row 5 K DEEP, column 6: CASF-2016 ranking Predictive Index; Table 2 (ijms-21-08424-t002), row 6 K DEEP, column 6: CASF-2016 ranking Predictive Index; Table 2 (ijms-21-08424-t002), row 7 AK-score-single, column 6: CASF-2016 ranking Predictive Index; Table 2 (ijms-21-08424-t002), row 8 AK-score-single, column 6: CASF-2016 ranking Predictive Index; Table 2 (ijms-21-08424-t002), row 9 AK-score-single, column 6: CASF-2016 ranking Predictive Index; Table 2 (ijms-21-08424-t002), row 10 AK-score-single, column 6: CASF-2016 ranking Predictive Index; Table 2 (ijms-21-08424-t002), row 11 AK-score-ensemble, column 6: CASF-2016 ranking Predictive Index; context: Training uses 3,772 PDBbind-2016 refined-set complexes after removal of the 285-complex core test set. CASF separates scoring, ranking and docking power.; caveats: Learning rates define distinct evaluated configurations. Table 2 ensemble Pearson 0.812 is distinct from the 30-network ensemble Pearson 0.827 in Figure 3. Do not transfer the 285-complex scoring denominator to ranking or docking rows without their appropriate grouping. Origins are labelled per method; appearance in one table does not constitute independent replication of every model.; review: method: automated_source_review; date: 2026-09-17
benchmark research: review date: 2026-09-17; status: complete_tables_extracted; primary sources: akscore-2020; inspected locators: A comparison of prediction accuracy with the CASF-2016 dataset.; Table 2 (ijms-21-08424-t002), row 3 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 4 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 5 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 6 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 7 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 8 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 9 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 10 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 11 AK-score-ensemble, column 4: CASF-2016 ranking Spearman correlation; searched queries: AK-Score: Accurate Protein-Ligand Binding Affinity Prediction Using an Ensemble of 3D-Convolutional Neural Networks 10.3390/ijms21228424; gaps: exact checkpoint hashes and per-method scored denominators: Table labels alone do not establish these fields; do not infer checkpoint or scored count from model name or dataset size.; claim scope: Dated primary-source discovery and protocol/table screening. Source checking does not mean experimental reproduction. Only separately extracted and independently reviewed numeric batches are publishable.
legacy kinds: benchmark
entity classification: review date: 2026-09-17; rationale: The source-backed record identifies a specified evaluated procedure and its dataset/split/scoring context. Classify it as a protocol while preserving version and comparison restrictions.; source ids: akscore-2020; source locator: A comparison of prediction accuracy with the CASF-2016 dataset.; Table 2 (ijms-21-08424-t002), row 3 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 4 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 5 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 6 K DEEP, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 7 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 8 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 9 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 10 AK-score-single, column 4: CASF-2016 ranking Spearman correlation; Table 2 (ijms-21-08424-t002), row 11 AK-score-ensemble, column 4: CASF-2016 ranking Spearman correlation; ambiguities: None recorded

Related records

evaluates task: Protein–ligand binding affinity scoring
subject: CASF-2016 ranking (Protein–ligand binding affinity scoring): links:evaluates_task:reported-task-a78312d5df6dad
benchmark: K DEEP · 0.0010: CASF-2016 ranking
benchmark: AK-score-single · 0.0010: CASF-2016 ranking
benchmark: AK-score-single · 0.0007: CASF-2016 ranking
benchmark: K DEEP · 0.0001: CASF-2016 ranking
benchmark: K DEEP · 0.0005: CASF-2016 ranking
benchmark: AK-score-single · 0.0001: CASF-2016 ranking
benchmark: K DEEP · 0.0006: CASF-2016 ranking
benchmark: AK-score-single · 0.0005: CASF-2016 ranking
benchmark: AK-score-ensemble · 0.0007: CASF-2016 ranking

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