{"id":"W2077046074","doi":"10.1021/ci034147w","title":"Inductive Electronegativity Scale. Iterative Calculation of Inductive Partial Charges","year":2003,"lang":"en","type":"article","venue":"Journal of Chemical Information and Computer Sciences","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Electronegativity; Inductive effect; Scale (ratio); Computer science; Statistical physics; Physics; Chemistry; Quantum mechanics; 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":[0.0006773398,0.0004318723,0.0004116979,0.0005114236,0.0001720035,0.0005127633,0.001045496,0.0003838324,0.002568265],"category_scores_gemma":[0.002132603,0.0001956342,0.0005669876,0.0003980417,0.0003591411,0.0008716547,0.0007745879,0.0005654848,0.0004751708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003768406,"about_ca_system_score_gemma":0.0003797482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005136685,"about_ca_topic_score_gemma":0.0004640328,"domain_scores_codex":[0.9997688,0.00007173734,0.00001261232,0.00002355905,0.0001011381,0.00002204653],"domain_scores_gemma":[0.9995757,0.0002149323,0.0000489641,0.00006769261,0.0000794152,0.00001342123],"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":[0.00007420278,0.00006834472,0.001658834,0.0001937118,0.0000661073,0.0001266505,0.00008076835,0.7896255,0.01836561,0.07837987,0.001015379,0.110345],"study_design_scores_gemma":[0.00001080334,0.00004674688,0.0005279054,0.00000593094,0.000009360144,0.00004254055,0.00001048226,0.976703,0.005032046,0.01635261,0.00124639,0.00001222586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04907829,0.0002171444,0.9429496,0.0000796675,0.0000256173,0.0001486473,0.0001356504,0.0004480479,0.006917264],"genre_scores_gemma":[0.7603971,0.0002628329,0.2357077,0.00008236072,0.00003195804,0.0003914227,0.0002968391,0.0001026949,0.002727004],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002568265,"threshold_uncertainty_score":0.008591712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01194296355221403,"score_gpt":0.2607042645147699,"score_spread":0.2487613009625559,"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."}}