{"id":"W2757851334","doi":"10.2174/2213476x03666160112001136","title":"Product Life Cycle Management for Pharmaceutical Innovation","year":2015,"lang":"en","type":"article","venue":"Applied Clinical Research Clinical Trials and Regulatory Affairs","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scrutiny; Commercialization; Product lifecycle; Business; Product (mathematics); New product development; Scope (computer science); Biosimilar; Product life-cycle management; Phase (matter); Competition (biology); Pharmaceutical industry; Marketing; Industrial organization; Computer science","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2093348,0.0002684529,0.001239975,0.0003471046,0.0002848834,0.0003368889,0.001182383,0.0003107325,0.00001311704],"category_scores_gemma":[0.05554574,0.0002147679,0.0003643131,0.001449818,0.001039968,0.0003287244,0.001337937,0.001048968,0.00006464851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007212949,"about_ca_system_score_gemma":0.0009019835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001551207,"about_ca_topic_score_gemma":6.832601e-7,"domain_scores_codex":[0.9851658,0.006679135,0.0039597,0.00169157,0.001716479,0.0007872991],"domain_scores_gemma":[0.9441596,0.05059191,0.0007486613,0.001548751,0.001375199,0.001575902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0008176849,0.0004921483,0.0001833543,0.00005240469,0.0001771891,0.000004893137,0.000028963,0.0003353509,0.00001360859,0.5559732,0.01424936,0.4276718],"study_design_scores_gemma":[0.01292476,0.0009402356,0.01047443,0.00006753461,0.00009514438,0.000004016245,0.0003946816,0.09402849,0.0002133129,0.7364598,0.1437744,0.0006232274],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1863348,0.001524193,0.7305533,0.03213707,0.007212969,0.01172216,0.00003711969,0.0006828211,0.02979557],"genre_scores_gemma":[0.8809586,0.0003409185,0.1145002,0.0009134996,0.002541933,0.000394493,0.0000165586,0.00003752892,0.000296314],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6946237,"threshold_uncertainty_score":0.9524098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6685465453233798,"score_gpt":0.6240170960708625,"score_spread":0.04452944925251723,"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."}}