{"id":"W3176284611","doi":"10.4095/328074","title":"Analyse des relations entre le climat et les séries temporelles de densité de cerne","year":2021,"lang":"en","type":"report","venue":"","topic":"Greenhouse Technology and Climate Control","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Humanities; Physics; Art","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006188417,0.0002802607,0.0004557514,0.00003437577,0.0005448531,0.00009634253,0.0002892068,0.0009168351,0.001777456],"category_scores_gemma":[0.0004137121,0.0001130834,0.0003155909,0.0003107176,0.0002337174,0.00007992777,0.0001706657,0.0005378785,0.00004423231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001822481,"about_ca_system_score_gemma":0.000389969,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007270031,"about_ca_topic_score_gemma":0.09373522,"domain_scores_codex":[0.9983263,0.0001732973,0.0003777426,0.0004199549,0.0002480175,0.0004546606],"domain_scores_gemma":[0.9989142,0.0003636559,0.0002105565,0.000124033,0.0002836638,0.0001038482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000229107,0.0002693511,0.9084938,0.00007208504,0.0003788213,0.0002657952,0.0002941068,0.00001859845,0.02189064,0.003765426,0.03178075,0.03274777],"study_design_scores_gemma":[0.0003772985,0.0002189883,0.7663296,0.0004097587,0.0006667514,0.0007605476,0.0180081,0.0000862446,0.005796766,0.009372797,0.1967742,0.001198883],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.928233,0.005804419,0.00004394758,0.005201879,0.00007205649,0.0001646124,0.0001005699,0.0005041867,0.05987533],"genre_scores_gemma":[0.9731546,0.007398717,0.0005866651,0.0001744095,0.0001407414,0.00003106805,0.0004749685,0.000004049837,0.01803477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1649935,"threshold_uncertainty_score":0.9993407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0379963832994145,"score_gpt":0.2626227185032524,"score_spread":0.2246263352038379,"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."}}