{"id":"W1980840780","doi":"10.1002/minf.201100111","title":"An Advanced Group Contribution Method for High‐Dimensional, Sparse Data Sets","year":2011,"lang":"en","type":"article","venue":"Molecular Informatics","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Group (periodic table); Computer science; Data mining; Chemistry; Organic chemistry","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":[0.003859253,0.001199534,0.001681035,0.002230957,0.0007426165,0.001077743,0.00226411,0.001732865,0.003129535],"category_scores_gemma":[0.009170289,0.0005684369,0.001809251,0.002415483,0.0009036572,0.001475528,0.001999244,0.002323466,0.001521012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004955071,"about_ca_system_score_gemma":0.001550864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003034087,"about_ca_topic_score_gemma":0.00262175,"domain_scores_codex":[0.9982252,0.0008080755,0.00008386744,0.0002575273,0.0005614022,0.00006386909],"domain_scores_gemma":[0.9968944,0.002028664,0.0001839457,0.0003134847,0.0004921202,0.00008735859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002451023,0.0001423403,0.001331992,0.0003376058,0.0002891918,0.0002420683,0.0002003778,0.4163024,0.008020769,0.02887546,0.006691666,0.537321],"study_design_scores_gemma":[0.00001115548,0.00002511304,0.0001091433,0.000008882663,0.000009897304,0.0000405765,0.00000718037,0.9899387,0.0005573293,0.007317387,0.001965168,0.000009478088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001493873,0.0001596582,0.9977635,0.00007900609,0.00003425356,0.00002796689,0.00004000804,0.0002190624,0.0001827649],"genre_scores_gemma":[0.06209595,0.0004809751,0.9337327,0.0001514316,0.000179686,0.0003696156,0.0005261255,0.0001859082,0.002277609],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003859253,"threshold_uncertainty_score":0.02040994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04836593607333022,"score_gpt":0.3458207124614303,"score_spread":0.2974547763881001,"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."}}