{"id":"W4393777810","doi":"10.5281/zenodo.6032538","title":"SuperDARN data in netCDF format (2018-Sep)","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; Meteorology; Computer graphics (images); Geology; Geography; 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":[0.0009383148,0.001467909,0.0009870919,0.002934934,0.0006839429,0.002354274,0.002244358,0.001657759,0.1425527],"category_scores_gemma":[0.005093686,0.0005439114,0.001173132,0.00430568,0.0003416919,0.00196713,0.001973867,0.001741219,0.208113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001398323,"about_ca_system_score_gemma":0.001765965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01665921,"about_ca_topic_score_gemma":0.02555852,"domain_scores_codex":[0.9992216,0.00009836135,0.00010546,0.0002184333,0.0002222789,0.0001339757],"domain_scores_gemma":[0.9981821,0.0003379551,0.0001460365,0.0004927272,0.0006937698,0.0001476],"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":[0.00003148234,0.00001041703,0.0004278465,0.0002494277,0.00001189022,0.00001600368,0.00001449309,0.0001728442,0.0000930543,0.0003872935,0.9962718,0.00231343],"study_design_scores_gemma":[0.00006718344,0.000006430126,0.0020523,0.0001577873,0.000009378943,0.00003941572,0.00006639351,0.0002319267,0.0003273063,0.001352234,0.9956722,0.00001746498],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009853276,0.00003423038,0.0001910865,0.00006729335,0.00004367656,0.00001180396,0.9975551,0.0008072311,0.001191051],"genre_scores_gemma":[0.0003142447,0.00003574538,0.0005089203,0.0000469551,0.000009368461,0.00004469763,0.9978285,0.0002339943,0.0009776102],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1425527,"threshold_uncertainty_score":0.4768863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08115749804266403,"score_gpt":0.3246934002755402,"score_spread":0.2435359022328761,"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."}}