{"id":"W34596745","doi":"","title":"Computational chemistry in the 1950s.","year":2001,"lang":"en","type":"article","venue":"PubMed","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Chemistry; Computational 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001244011,0.00009062744,0.00007490889,0.000007776467,0.00006680632,0.00001773975,0.0002804051,0.00005660855,0.001005099],"category_scores_gemma":[0.00005546072,0.00007605967,0.00003601738,0.0001001453,0.00006393171,0.00005483884,0.00002331615,0.0001932613,0.00001495339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008827508,"about_ca_system_score_gemma":0.00001437344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002344136,"about_ca_topic_score_gemma":8.916755e-7,"domain_scores_codex":[0.9992211,0.000006267413,0.0001559884,0.0001741972,0.0001989103,0.0002435043],"domain_scores_gemma":[0.9996203,0.00007375648,0.00004432367,0.0002038612,0.00001364552,0.00004413655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004027743,0.002885297,0.1052744,0.001176614,0.0001965625,0.001293106,0.003230431,0.01518367,0.02569631,0.000939605,0.04019265,0.8035286],"study_design_scores_gemma":[0.001107339,0.000001014348,0.008550086,0.00001719985,0.00001218641,0.0001241785,0.0005078524,0.0001408728,0.01591897,0.002859137,0.9704382,0.0003229569],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5116087,0.0002158426,0.0000315849,0.0003463647,0.00004800615,0.00006114288,0.000008237535,0.00004261466,0.4876375],"genre_scores_gemma":[0.9878224,0.0000123495,0.00006913104,0.0002855166,0.0001974113,0.000481073,0.00004079079,0.000008279282,0.01108302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9302456,"threshold_uncertainty_score":0.9999081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0198280716038906,"score_gpt":0.225077732248692,"score_spread":0.2052496606448014,"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."}}