{"id":"W4393516141","doi":"10.5281/zenodo.6808553","title":"SuperDARN data in netCDF format (1998-May)","year":2022,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced X-ray Imaging Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"NetCDF; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007570076,0.0003058763,0.0003128255,0.0004246687,0.001342016,0.0006273583,0.004418146,0.00006984517,0.1272467],"category_scores_gemma":[0.000146819,0.0003525224,0.0000589299,0.00061961,0.000141417,0.000625425,0.009378255,0.001129098,0.003960425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000207148,"about_ca_system_score_gemma":0.00001286011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003101562,"about_ca_topic_score_gemma":0.000001452533,"domain_scores_codex":[0.9974068,0.0003554606,0.0004248539,0.0007687867,0.0004968349,0.0005472058],"domain_scores_gemma":[0.9972691,0.00003558292,0.0002060249,0.002225357,0.0001276426,0.0001362851],"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":[0.00002030417,0.0001548638,0.000004204625,0.0000552974,0.00003307353,0.00001498756,0.00008491472,0.00001839579,0.0000173634,0.000315844,0.9716969,0.02758385],"study_design_scores_gemma":[0.0003332078,0.00008091881,0.00001099905,0.00003957705,0.00002222422,0.0000168895,0.0001840539,0.0001213158,0.00002113378,0.0005232741,0.9983019,0.0003444536],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004154664,0.0000617072,0.001833633,0.0002045029,0.000130686,0.0005845695,0.986115,0.0005242951,0.01050405],"genre_scores_gemma":[0.0008181095,0.00008709268,0.0004538445,0.00009883226,0.0002239923,2.428383e-7,0.9967663,0.001263489,0.0002880565],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1232863,"threshold_uncertainty_score":0.9999581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04464437386157261,"score_gpt":0.2966427686541019,"score_spread":0.2519983947925293,"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."}}