{"id":"W4293311533","doi":"","title":"Rapport de première année AGREV3","year":2018,"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":false,"ca_institutions":"ASTER","funders":"","keywords":"Artificial intelligence; Computer science","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":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.0029546,0.001730159,0.0015726,0.0001312853,0.001544913,0.0008071443,0.003089481,0.002075385,0.01001404],"category_scores_gemma":[0.0005469471,0.0007729461,0.0009372489,0.001584876,0.001138382,0.0005581103,0.003373248,0.002332037,0.004877895],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006596507,"about_ca_system_score_gemma":0.0008323516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008294645,"about_ca_topic_score_gemma":0.0005736483,"domain_scores_codex":[0.9895106,0.0007529508,0.001660433,0.002807832,0.001798302,0.003469881],"domain_scores_gemma":[0.9952962,0.0003831974,0.00081599,0.0006904843,0.00146137,0.001352756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005237942,0.001764994,0.1456308,0.001324309,0.0008603286,0.0004863238,0.002394186,0.00007432212,0.02423447,0.02103726,0.6385477,0.1631214],"study_design_scores_gemma":[0.0006146172,0.00131352,0.1699241,0.001009528,0.0002522921,0.0002262556,0.002565761,0.0003679991,0.003526666,0.01398883,0.8036036,0.002606817],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7382458,0.01095356,0.0002490309,0.1303243,0.004233662,0.006468115,0.0005580544,0.000979631,0.1079879],"genre_scores_gemma":[0.5721602,0.007050392,0.003602842,0.001046179,0.01287273,0.0009448173,0.002706753,0.00004999782,0.3995661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2915783,"threshold_uncertainty_score":0.9999696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0326780819544845,"score_gpt":0.2668010799841217,"score_spread":0.2341229980296372,"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."}}