{"id":"W6946130877","doi":"10.26023/akwd-brv8-r80d","title":"WINTRE-MIX: CFI Climate Sentinels Gault MRR-2 Processed Data. Version 1.0","year":2022,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université du Québec à Montréal","funders":"","keywords":"Radar; Precipitation; Climate change; Elevation (ballistics); Doppler radar; Profiling (computer programming)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0009667575,0.002391921,0.001204082,0.002375093,0.0008378772,0.00192688,0.003388115,0.002246859,0.03034862],"category_scores_gemma":[0.003079258,0.0006167561,0.001074651,0.004215958,0.0004549146,0.001066441,0.001590978,0.001630129,0.05781665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001945676,"about_ca_system_score_gemma":0.003114027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1023352,"about_ca_topic_score_gemma":0.1788453,"domain_scores_codex":[0.9991773,0.00009864425,0.00007350619,0.0002351375,0.0002351617,0.0001803543],"domain_scores_gemma":[0.9986418,0.0002520243,0.0001296638,0.000312627,0.0004909787,0.000172928],"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":[0.00008617935,0.00002852831,0.001538189,0.0004790674,0.00004364746,0.00004361276,0.00003554515,0.0007388906,0.0004040291,0.000376726,0.9936236,0.002602102],"study_design_scores_gemma":[0.0002521825,0.00002512098,0.008976714,0.0002555599,0.00004177594,0.00006768907,0.000119109,0.00159843,0.001058558,0.001222722,0.986315,0.00006718742],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000157209,0.0000311681,0.00007013913,0.00002810995,0.00001347662,0.000008146425,0.9989367,0.0004797759,0.0002752804],"genre_scores_gemma":[0.0003549508,0.00001940292,0.000263323,0.00002158652,0.000003058806,0.00003322617,0.9989794,0.00008547518,0.0002396065],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1023352,"threshold_uncertainty_score":0.203479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02500031136828212,"score_gpt":0.3379423940983399,"score_spread":0.3129420827300578,"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."}}