{"id":"W4393799791","doi":"10.5281/zenodo.5951221","title":"Wallops SuperDARN data in netCDF format (2020-Feb)","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; Geology; Computer science; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009070011,0.001330036,0.0008795387,0.002659123,0.000764336,0.00289347,0.001959538,0.001618344,0.2997038],"category_scores_gemma":[0.003985373,0.0007193403,0.0009233921,0.00437574,0.0002787386,0.002547909,0.001925735,0.00177976,0.3266725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00133157,"about_ca_system_score_gemma":0.001703421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02479334,"about_ca_topic_score_gemma":0.02658336,"domain_scores_codex":[0.9993145,0.00005875148,0.00006866668,0.0001380695,0.00027109,0.0001488568],"domain_scores_gemma":[0.9979989,0.0002184127,0.0001680884,0.0004792052,0.0009358907,0.0001994288],"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":[0.00004319281,0.000008773462,0.0003150838,0.0001122192,0.000006660865,0.00001656415,0.00001193141,0.000158778,0.0001337559,0.0003021419,0.9963092,0.002581688],"study_design_scores_gemma":[0.00008506503,0.000007915617,0.002396237,0.0001054518,0.000007014921,0.0000275777,0.00006638817,0.0002538285,0.0005012473,0.00088594,0.9956405,0.0000228887],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001909943,0.0000247611,0.0002758714,0.0001148528,0.0001254829,0.0000190729,0.9929288,0.001459735,0.004860407],"genre_scores_gemma":[0.0006742618,0.00003745897,0.0008113085,0.00007186317,0.00002674165,0.00005267308,0.9936319,0.0009365493,0.003757332],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2997038,"threshold_uncertainty_score":0.9988875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05928363581707396,"score_gpt":0.3166712592487722,"score_spread":0.2573876234316982,"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."}}