{"id":"W6931570866","doi":"10.5683/sp3/smmdpx","title":"Données relatives au mémoire Modélisation numérique du système aquifère régional appalachien du bassin versant de la rivière Saint-François, Québec, Canada","year":2023,"lang":"fr","type":"dataset","venue":"Borealis","topic":"Retinal Development and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Chine; Agriculture; Drainage basin","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":[0.001626077,0.002381323,0.001583929,0.004171597,0.002177273,0.002594157,0.003680176,0.002312948,0.03729104],"category_scores_gemma":[0.01289026,0.0007864509,0.002298564,0.007990764,0.0007359911,0.0008741461,0.00137859,0.00182546,0.02016399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00978267,"about_ca_system_score_gemma":0.01606345,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8676963,"about_ca_topic_score_gemma":0.9185107,"domain_scores_codex":[0.9985173,0.0002351669,0.0001314643,0.0003883655,0.0005170414,0.0002106397],"domain_scores_gemma":[0.994226,0.001933185,0.0001953127,0.0007371578,0.002621374,0.0002869478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001132945,0.00003129402,0.00423905,0.001518512,0.0001925208,0.00008856299,0.00009850346,0.005555378,0.000243622,0.001066027,0.9791669,0.007686327],"study_design_scores_gemma":[0.0004385076,0.00002191714,0.02246779,0.0008791413,0.0001725904,0.00009911731,0.0002551528,0.007730197,0.0006971816,0.002274875,0.964865,0.00009849757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006533985,0.0004221018,0.0003051409,0.000145274,0.00003025912,0.00001790282,0.9965872,0.0005532005,0.001285588],"genre_scores_gemma":[0.002837331,0.0003076521,0.0009526814,0.00005871245,0.000008120555,0.00009534454,0.9939789,0.00008568451,0.001675603],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1323037,"threshold_uncertainty_score":0.2661657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006251741209568839,"score_gpt":0.207372835861477,"score_spread":0.2011210946519081,"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."}}