{"id":"W2032245355","doi":"10.1021/jm0497141","title":"A Comparison of Methods for Modeling Quantitative Structure−Activity Relationships","year":2004,"lang":"en","type":"article","venue":"Journal of Medicinal Chemistry","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":231,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Dalhousie University","funders":"","keywords":"Quantitative structure–activity relationship; Partial least squares regression; Chemistry; Test set; Artificial neural network; Molecular descriptor; Artificial intelligence; Biological system; Pattern recognition (psychology); Machine learning; Computer science; Stereochemistry","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":[0.008061958,0.001385079,0.001316271,0.003489529,0.0003661639,0.001283051,0.00156145,0.00101833,0.00172734],"category_scores_gemma":[0.0126992,0.0005250428,0.001710877,0.002359826,0.0003885459,0.001474923,0.0008594184,0.001044673,0.0005636656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00104292,"about_ca_system_score_gemma":0.001271033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003953871,"about_ca_topic_score_gemma":0.003315883,"domain_scores_codex":[0.9955249,0.001658997,0.000303819,0.0002722118,0.002131645,0.0001084729],"domain_scores_gemma":[0.9902309,0.007531313,0.0004010794,0.0007781914,0.0009709358,0.00008756707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004954193,0.0002659376,0.005064945,0.0009856803,0.0009255086,0.00007089839,0.0001438281,0.6498922,0.004132695,0.02169858,0.001747952,0.3145764],"study_design_scores_gemma":[0.00005965158,0.0002511148,0.001580255,0.00008643768,0.00007984822,0.00008272614,0.00002876006,0.9849791,0.00188216,0.007284859,0.003638064,0.00004705383],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05490603,0.01284698,0.9210434,0.0006175639,0.0002036453,0.0002674494,0.0009514184,0.00231261,0.006850956],"genre_scores_gemma":[0.3834246,0.01494706,0.5952068,0.0002123399,0.0001880919,0.0009951902,0.001794605,0.0006091436,0.00262233],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008061958,"threshold_uncertainty_score":0.04263622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.171726358508559,"score_gpt":0.4889138672521705,"score_spread":0.3171875087436115,"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."}}