{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001415576,0.000182706,0.0002200325,0.0001190724,0.000122646,0.0001171437,0.00159715,0.00007386776,0.000006959555],"category_scores_gemma":[0.0002637843,0.0001794074,0.00005533674,0.0002782481,0.00003063471,0.002380377,0.0006099426,0.0001082274,0.00002324557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004611455,"about_ca_system_score_gemma":0.000104741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000183683,"about_ca_topic_score_gemma":0.000003582053,"domain_scores_codex":[0.9983164,0.0001805255,0.0005183457,0.0002732468,0.000401124,0.0003103383],"domain_scores_gemma":[0.9976594,0.0002240806,0.0002476307,0.001474865,0.000258335,0.0001356219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006900952,0.0002407967,0.00001237126,0.00006502434,0.00008332882,0.00001626143,0.001141347,0.05764957,0.002494192,0.7394705,0.0006153669,0.1981423],"study_design_scores_gemma":[0.0006955025,0.0001657344,0.000487951,0.00001501326,0.00002129747,0.00002113065,0.00003138798,0.9396367,0.008070864,0.0493638,0.001254574,0.0002360607],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02157065,0.00003533197,0.9770817,0.0000862938,0.0002860799,0.0004827639,0.0001100775,0.0001342374,0.0002129214],"genre_scores_gemma":[0.1504334,0.000001632798,0.8478223,0.001042989,0.00001304829,0.00002959242,0.000643139,0.00001130494,0.000002586796],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8819871,"threshold_uncertainty_score":0.7316023,"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."}}