{"id":"W2732344505","doi":"","title":"Analyser le fonctionnement des multiples populations pour mettre en évidence les empreintes des changements écosystémiques","year":2015,"lang":"fr","type":"preprint","venue":"Prodinra (INRA Bordeaux-Aquitaine)","topic":"Agriculture and Rural Development Research","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Analyser; Physics; Optics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001939766,0.0009761317,0.001127261,0.001735047,0.0004703399,0.001953691,0.0007957811,0.001305584,0.005257806],"category_scores_gemma":[0.00646871,0.0003101894,0.001416605,0.001379008,0.000444619,0.001881749,0.0004784094,0.001085227,0.001237328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006913461,"about_ca_system_score_gemma":0.0004718252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009477553,"about_ca_topic_score_gemma":0.008406774,"domain_scores_codex":[0.9988955,0.0002789613,0.00004506932,0.0004479155,0.0002373081,0.0000951908],"domain_scores_gemma":[0.9934775,0.004702038,0.0004922168,0.0004513541,0.0006492598,0.0002276622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001369037,0.0004588306,0.3537813,0.0006477489,0.001507561,0.0009591075,0.001183382,0.2257925,0.08081948,0.003495758,0.003118579,0.3268667],"study_design_scores_gemma":[0.00007434242,0.0006986992,0.3394503,0.00008919082,0.000519672,0.001073652,0.00114455,0.6249213,0.02050178,0.005967878,0.005429174,0.0001294147],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9017336,0.001269493,0.09153955,0.0005501126,0.0001518946,0.00004594106,0.001380436,0.0008025666,0.00252639],"genre_scores_gemma":[0.9692668,0.0003013637,0.02577916,0.00006043758,0.00008719212,0.00005642607,0.0009267194,0.0001481287,0.003373718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009477553,"threshold_uncertainty_score":0.01884478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1425122856903701,"score_gpt":0.3274123573149684,"score_spread":0.1849000716245983,"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."}}