{"id":"W4393765582","doi":"10.5281/zenodo.7650952","title":"SuperDARN Grid data in netCDF format (2010-Jul)","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"NetCDF; Grid; Computer science; Database; Computer graphics (images); Geology; Operating system; Geodesy","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","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["open_science"],"category_scores_codex":[0.00204983,0.000324985,0.0003781458,0.000589052,0.001251669,0.002703954,0.01228327,0.0002140627,0.0007335515],"category_scores_gemma":[0.0007496244,0.0003433514,0.00006340436,0.001586461,0.00009667681,0.0007751095,0.01380237,0.0008030421,0.06769336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001786293,"about_ca_system_score_gemma":0.00002052473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004169039,"about_ca_topic_score_gemma":0.000009963944,"domain_scores_codex":[0.9961478,0.0006101379,0.0005978124,0.001109057,0.0007789191,0.0007562582],"domain_scores_gemma":[0.9956209,0.00007719664,0.0002309891,0.003521249,0.0003171072,0.0002325299],"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":[0.000008160665,0.00007873466,4.410977e-7,0.0001682138,0.00002934016,0.00009406395,0.0001426519,0.0001212492,0.000003382583,0.0002352688,0.9920611,0.007057337],"study_design_scores_gemma":[0.0003680878,0.0001018009,0.00008564077,0.0001468834,0.000008809655,0.0001522022,0.00003652178,0.006634428,9.503936e-7,0.00006412356,0.992044,0.0003565705],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000170938,0.0001177968,0.01070147,0.0005747299,0.001607007,0.0005101489,0.9825547,0.001368932,0.002548164],"genre_scores_gemma":[0.0002578113,0.0002141456,0.000192615,0.0001226134,0.0004680977,5.548159e-8,0.9976083,0.000681064,0.0004552694],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06695981,"threshold_uncertainty_score":0.9999018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07578310433557811,"score_gpt":0.2740746587739161,"score_spread":0.198291554438338,"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."}}