{"id":"W7128564563","doi":"","title":"GIPS-1 : Matériau de référence de racine de ginseng pour les traces de métaux et de pesticides","year":2016,"lang":"","type":"other","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ginseng; Pesticide; TRACE (psycholinguistics); American ginseng; Trace metal","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":[],"consensus_categories":[],"category_scores_codex":[0.001578599,0.00134578,0.0004628431,0.00366534,0.001321216,0.001074433,0.001179281,0.001461339,0.01288405],"category_scores_gemma":[0.001881666,0.0004164219,0.0004050141,0.001233132,0.0008305942,0.001028155,0.0008772317,0.0009300839,0.006521238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008657962,"about_ca_system_score_gemma":0.001722243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003105697,"about_ca_topic_score_gemma":0.005832811,"domain_scores_codex":[0.9973464,0.0002404229,0.0001067108,0.0004680688,0.001706503,0.0001318869],"domain_scores_gemma":[0.9993116,0.000103686,0.0001168289,0.0001375547,0.0002931263,0.00003720248],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006352926,0.000116472,0.00194982,0.001218383,0.00005269722,0.0006675601,0.0004259953,0.0005351524,0.8413135,0.006893156,0.01804439,0.1281477],"study_design_scores_gemma":[0.00004746198,0.0003233755,0.004875864,0.000218957,0.0000696676,0.001256213,0.0001675324,0.0008902056,0.6221673,0.0009869076,0.3689498,0.00004665656],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.4438669,0.03099454,0.1842048,0.001221464,0.002974654,0.002941587,0.02794261,0.01061548,0.295238],"genre_scores_gemma":[0.6309971,0.01042274,0.1676755,0.0007794014,0.0003616384,0.001597885,0.02918868,0.001783857,0.1571931],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.01288405,"threshold_uncertainty_score":0.04310143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06503262729510619,"score_gpt":0.3848485271950612,"score_spread":0.319815899899955,"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."}}