{"id":"W7098733227","doi":"","title":"Acquisitions and Acquisitions et Bibliographie Services services bibliographiques","year":2015,"lang":"en","type":"article","venue":"","topic":"Medicinal Plant Extracts Effects","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Habitat; Information system; Term (time)","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.0006411072,0.0002808008,0.0003968865,0.01294515,0.0001208712,0.0001525593,0.0001403562,0.0001676788,0.0002716057],"category_scores_gemma":[0.00001740571,0.0002161793,0.0001089789,0.01076974,0.0001612173,0.0006936525,0.0000935522,0.0002451745,0.000108663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001153835,"about_ca_system_score_gemma":0.00005615443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001405751,"about_ca_topic_score_gemma":0.0006279175,"domain_scores_codex":[0.9982169,0.0001044384,0.0003172389,0.0004170516,0.0005663647,0.0003780059],"domain_scores_gemma":[0.9980623,0.0002233811,0.0001010228,0.0004151597,0.0003371409,0.0008610057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00134828,0.002008179,0.6831834,0.005008313,0.001280181,0.001520353,0.004907247,0.00001771833,0.03483205,0.02204379,0.2408547,0.002995821],"study_design_scores_gemma":[0.008940484,0.003890025,0.8610662,0.003244163,0.001636213,0.004453734,0.008949122,0.002175473,0.003960194,0.01362367,0.08666996,0.001390719],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9182277,0.003996965,0.0002269231,0.006923522,0.0001951431,0.0006615968,0.00008175957,0.0006244454,0.06906199],"genre_scores_gemma":[0.9766464,0.003640895,0.002841825,0.01586602,0.0002435167,0.00004590167,0.0003306548,0.00003602939,0.0003487759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1778829,"threshold_uncertainty_score":0.9982423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02391912008029561,"score_gpt":0.3154311750341166,"score_spread":0.2915120549538209,"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."}}