{"id":"W2519311317","doi":"10.2533/chimia.2016.662","title":"Thematic Platform in vitro Diagnostics Technological Progress with a Powerful Network","year":2016,"lang":"en","type":"article","venue":"CHIMIA International Journal for Chemistry","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"World Federation of Science Journalists","funders":"","keywords":"Thematic map; Population; Business; Biotechnology; Engineering; Data science; Nanotechnology; Medicine; Computer science; Biology; Geography; Environmental health; Cartography","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":[],"consensus_categories":[],"category_scores_codex":[0.0003635859,0.0001598245,0.0002276759,0.00004047953,0.00006687714,0.00003386618,0.0004679226,0.0002905421,0.0003834329],"category_scores_gemma":[0.0004980508,0.000081464,0.0001114217,0.00007605753,0.0003713208,0.00006666688,0.00007872945,0.0003558556,0.00001271978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001083796,"about_ca_system_score_gemma":0.00005210485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.467065e-7,"about_ca_topic_score_gemma":5.718762e-7,"domain_scores_codex":[0.9990399,0.00001904225,0.0003266401,0.0001956504,0.00008120629,0.0003374948],"domain_scores_gemma":[0.9990439,0.0004791133,0.0001717922,0.0001190092,0.0001482362,0.00003795534],"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":[0.004211149,0.0007890417,0.01653453,0.00007262267,0.001170643,0.0002341361,0.00005174799,0.000004838178,0.7866615,0.002187397,0.008477457,0.1796049],"study_design_scores_gemma":[0.00467004,0.0001962089,0.001674085,0.0007653324,0.00007260921,0.002209523,0.0001304923,0.00002469831,0.9510087,0.01227304,0.02658514,0.000390118],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9713523,0.002300224,0.01065011,0.01170774,0.001453147,0.0004252278,0.000139742,0.00009977126,0.001871678],"genre_scores_gemma":[0.991967,0.0002055282,0.006205078,0.0001701621,0.0002327813,0.00002876987,0.00001652265,0.00001558219,0.001158524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1792148,"threshold_uncertainty_score":0.4198321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0161835316574426,"score_gpt":0.2910298786039191,"score_spread":0.2748463469464765,"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."}}