{"id":"W4241342873","doi":"10.3410/f.1022074.292795","title":"Faculty Opinions recommendation of Phagemid encoded small molecules for high throughput screening of chemical libraries.","year":2005,"lang":"en","type":"dataset","venue":"Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Throughput; High-throughput screening; Computer science; Chemistry; Computational biology; Combinatorial chemistry; Information retrieval; Biology; Telecommunications; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001583096,0.004149779,0.002381948,0.004529298,0.000784389,0.002736022,0.004088646,0.003331708,0.05107513],"category_scores_gemma":[0.006014544,0.001102707,0.001786597,0.006277477,0.0003302982,0.001394007,0.001393828,0.002305913,0.06279296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001759968,"about_ca_system_score_gemma":0.003600995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01883151,"about_ca_topic_score_gemma":0.04195136,"domain_scores_codex":[0.9984369,0.0001980345,0.0001639341,0.0004268076,0.0006032845,0.0001710204],"domain_scores_gemma":[0.9973157,0.0006968682,0.0003431031,0.0006207412,0.0006003402,0.0004231831],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002796219,0.000105837,0.001309403,0.001701454,0.0001136277,0.000045001,0.00001308832,0.000724481,0.0009006726,0.0003652995,0.9884717,0.005969811],"study_design_scores_gemma":[0.00104164,0.0001249012,0.008513332,0.0003779013,0.0002258886,0.0001221795,0.000040869,0.004338289,0.005881906,0.001462484,0.9778025,0.00006814089],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003150922,0.0001371592,0.0001775178,0.00006602229,0.00001992948,0.00002484886,0.9972959,0.001174035,0.0007895592],"genre_scores_gemma":[0.000444925,0.00006965987,0.000458565,0.00004207794,0.000002968289,0.00003624113,0.9984173,0.00005606426,0.0004722073],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05107513,"threshold_uncertainty_score":0.1708633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04008777971554453,"score_gpt":0.3454199076068783,"score_spread":0.3053321278913338,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}