{"id":"W2770785706","doi":"10.1021/cen-09029-meetings","title":"Bringing Materials Science To Pharma","year":2012,"lang":"en","type":"article","venue":"Chemical & Engineering News","topic":"Chemistry and Chemical Engineering","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Citation; Altmetrics; Social media; Computer science; Library science; Information retrieval; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000187763,0.0001978197,0.0001621196,0.00003180417,0.00004764179,0.00004423097,0.0004090443,0.00005889414,0.001345446],"category_scores_gemma":[0.0001926231,0.0002049315,0.00004163956,0.0004891693,0.00007220423,0.000320987,0.0004131311,0.0001459214,0.0005155873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002743693,"about_ca_system_score_gemma":0.000005076413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001907188,"about_ca_topic_score_gemma":3.332877e-8,"domain_scores_codex":[0.9984142,0.000001766808,0.0002005819,0.0003006898,0.0003020204,0.000780715],"domain_scores_gemma":[0.9990781,0.00002956647,0.00002124594,0.0002628427,0.000005420427,0.0006028364],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000002945826,0.00002199135,0.0003233828,0.0000172052,0.000002485693,0.000001128095,0.00008381273,0.002060549,0.9962958,0.00003741632,0.0005871673,0.0005661907],"study_design_scores_gemma":[0.00009525284,0.000002638031,0.0003745684,0.00002093396,0.000005674998,0.0000186165,0.000005426928,0.0006969556,0.9867806,0.000003952709,0.01172425,0.0002710959],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938012,0.00002405536,0.001598277,0.00007952325,0.000285401,0.00008058398,0.000002804195,0.000214198,0.003913911],"genre_scores_gemma":[0.9936012,0.000001473988,0.005744284,0.0001334315,0.000346301,0.00002173552,0.000003191968,0.00002858452,0.0001198197],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01113709,"threshold_uncertainty_score":0.9995674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006676722092074947,"score_gpt":0.2140676540498688,"score_spread":0.2073909319577938,"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."}}