{"id":"W2774511977","doi":"","title":"IMPURITY PROFILING OF ACTIVE PHARMACEUTICAL INGREDIENTS AND FINISHED DRUG PRODUCTS","year":2017,"lang":"en","type":"article","venue":"International Journal of Drug Research and Technology","topic":"Analytical Methods in Pharmaceuticals","field":"Chemistry","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Active ingredient; Impurity; Drug; Pharmaceutical drug; Pharmaceutical industry; Biochemical engineering; Pharmaceutical formulation; Profiling (computer programming); Chemistry; Chromatography; Pharmacology; Medicine; Organic chemistry; Computer science; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00164952,0.0006778157,0.0007360419,0.003420524,0.0004013618,0.001092104,0.0006980517,0.0008940771,0.001598602],"category_scores_gemma":[0.002528673,0.0002976544,0.0006221398,0.001629238,0.0004807457,0.000983522,0.0004745382,0.0008214731,0.00129819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004924897,"about_ca_system_score_gemma":0.0008567207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008431427,"about_ca_topic_score_gemma":0.001023633,"domain_scores_codex":[0.9972011,0.0004576785,0.0001801203,0.0003686373,0.00169142,0.0001011914],"domain_scores_gemma":[0.9987796,0.0003437569,0.000254758,0.00005273578,0.0005317492,0.00003736283],"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":[0.0003871212,0.0001951043,0.004486168,0.006395955,0.0002272174,0.000855983,0.0002712322,0.001693868,0.653873,0.004598956,0.003977185,0.3230383],"study_design_scores_gemma":[0.00001600443,0.0005522483,0.007538767,0.0006212278,0.0001806133,0.001951705,0.0001850393,0.004328745,0.8676226,0.001537309,0.1153984,0.00006738106],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1914735,0.38237,0.3504781,0.001439749,0.001056103,0.00155075,0.004019146,0.00163763,0.06597503],"genre_scores_gemma":[0.5142844,0.1809075,0.273249,0.00154405,0.0004745815,0.0005972818,0.002887004,0.0003601468,0.02569596],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003420524,"threshold_uncertainty_score":0.008723557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1098367406030158,"score_gpt":0.5020054071823202,"score_spread":0.3921686665793045,"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."}}