{"id":"W4393518961","doi":"10.5281/zenodo.6348016","title":"SuperDARN data in netCDF format (2016-Dec)","year":2022,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"NetCDF; Computer science; Geology; Programming language","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":[0.0009498395,0.001493275,0.0009854865,0.002939233,0.0006579304,0.002419318,0.002197093,0.001614705,0.136187],"category_scores_gemma":[0.005101362,0.0005466106,0.001166489,0.004349626,0.0003396712,0.001981394,0.001968544,0.001750642,0.2068104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001431515,"about_ca_system_score_gemma":0.001807826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01669886,"about_ca_topic_score_gemma":0.02620725,"domain_scores_codex":[0.9991837,0.0001030213,0.0001146179,0.000226607,0.0002360769,0.0001360016],"domain_scores_gemma":[0.9981798,0.0003286978,0.0001521048,0.0004977199,0.0006929414,0.0001488174],"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":[0.00003173322,0.000009996306,0.0004574819,0.0002598039,0.00001265753,0.00001522932,0.00001421171,0.0001860885,0.0000972015,0.0004139162,0.9961426,0.002359198],"study_design_scores_gemma":[0.0000639272,0.000006064972,0.001990252,0.0001587593,0.000009424803,0.00003864025,0.00006269409,0.0002292924,0.0003361896,0.001363201,0.9957242,0.00001738337],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009428754,0.00003451388,0.0001893669,0.00006499511,0.00004350676,0.00001108308,0.9976394,0.0007714292,0.001151456],"genre_scores_gemma":[0.0003084558,0.00003747117,0.000500078,0.00004650035,0.000009043963,0.00004097705,0.9978526,0.000234493,0.0009703982],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.136187,"threshold_uncertainty_score":0.455591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07398150717604846,"score_gpt":0.3233668292890652,"score_spread":0.2493853221130168,"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."}}