{"id":"W4403353876","doi":"10.22159/ajpcr.2024v17i10.52179","title":"STREAMLINING REGULATORY DOCUMENTATION: EXPLORING THE COMMON TECHNICAL DOCUMENT (CTD) AND ELECTRONIC SUBMISSION, WITH EMPHASIS ON M SERIES ACCORDING TO ICH GUIDELINES","year":2024,"lang":"en","type":"article","venue":"Asian Journal of Pharmaceutical and Clinical Research","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"CTD; Documentation; Emphasis (telecommunications); Series (stratigraphy); Computer science; Telecommunications; Biology; Programming language; Geology; Paleontology","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1944554,0.001503603,0.001533205,0.01240522,0.005609499,0.02550051,0.005831357,0.008074925,0.005652715],"category_scores_gemma":[0.3145448,0.001704219,0.002135538,0.01195885,0.02199131,0.0330946,0.01673882,0.01174879,0.005170475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01053379,"about_ca_system_score_gemma":0.0504177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007690223,"about_ca_topic_score_gemma":0.007636744,"domain_scores_codex":[0.6988789,0.1749047,0.04628386,0.009572074,0.06645396,0.003906587],"domain_scores_gemma":[0.5848768,0.2279923,0.05087199,0.05201477,0.07919647,0.005047625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001492019,0.0001953926,0.002340785,0.003515753,0.00005064357,0.0007548692,0.009880559,0.001154808,0.001963121,0.4909284,0.06826785,0.4207986],"study_design_scores_gemma":[0.0001448137,0.0005240447,0.002548559,0.009723368,0.0000998727,0.002407857,0.005656245,0.003430784,0.004493269,0.1905462,0.7801437,0.0002812182],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01262425,0.03446674,0.6046305,0.1415913,0.007913366,0.006352652,0.0006811349,0.00293585,0.1888042],"genre_scores_gemma":[0.1235611,0.03501348,0.738483,0.04700829,0.005976134,0.005460996,0.001296013,0.001709093,0.04149191],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1944554,"threshold_uncertainty_score":0.99338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3997167359349398,"score_gpt":0.6068757481174795,"score_spread":0.2071590121825397,"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."}}