{"id":"W2154473763","doi":"10.4155/bio.14.279","title":"2014 White Paper on Recent Issues in Bioanalysis: A Full Immersion in Bioanalysis (Part 2 – Hybrid LBA/LCMS, ELN & Regulatory Agencies’ Input)","year":2014,"lang":"en","type":"article","venue":"Bioanalysis","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"inVentiv Health Clinical; Health Canada; Armand Frappier Museum","funders":"","keywords":"Bioanalysis; Biopharmaceutical; Computer science; White paper; Nanotechnology; Engineering ethics; Political science; Engineering; Materials science; Biotechnology; Biology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.003982923,0.0009144699,0.002190096,0.00276558,0.0002841279,0.0001014862,0.0009662784,0.0008577455,0.01036368],"category_scores_gemma":[0.000549259,0.0007477606,0.001193098,0.003970024,0.0006807445,0.0002444492,0.0003323759,0.0009722834,0.00171456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005410758,"about_ca_system_score_gemma":0.0001137701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009169363,"about_ca_topic_score_gemma":0.004129523,"domain_scores_codex":[0.9918427,0.002500851,0.001972579,0.001897555,0.0004092743,0.001376974],"domain_scores_gemma":[0.9963183,0.0004623878,0.0006297441,0.002107312,0.0002718193,0.0002104806],"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":[0.004040628,0.006315856,0.2138653,0.0003624957,0.01876215,0.0002051123,0.001742339,0.001606207,0.1621317,0.001958673,0.1727515,0.416258],"study_design_scores_gemma":[0.002328537,0.0004532489,0.01657196,0.0002196566,0.002941736,0.00001868409,0.0009022023,0.0009904826,0.01306511,0.0004020795,0.9604872,0.001619062],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7268579,0.1783869,0.002905194,0.06121177,0.003697819,0.002327376,0.0006844494,0.0007919822,0.02313667],"genre_scores_gemma":[0.9598488,0.01429651,0.002967878,0.004244084,0.0002768649,0.00009474799,0.0007249095,0.000109782,0.01743644],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7877358,"threshold_uncertainty_score":0.9994974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0202534522797612,"score_gpt":0.2752489872493901,"score_spread":0.2549955349696288,"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."}}