{"id":"W4393522172","doi":"10.5281/zenodo.7823933","title":"SuperDARN Grid data in netCDF format (2018-Oct)","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; Grid cell; Computer science; Geology; Computer graphics (images); Database; Geodesy; Operating system","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":[0.002057933,0.0003249032,0.0003789862,0.0005859925,0.001248228,0.002717805,0.01226117,0.0002092534,0.0006597212],"category_scores_gemma":[0.0007369282,0.0003431149,0.00006324258,0.001606995,0.00009683304,0.0007740011,0.01384851,0.0007664918,0.06973962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000200072,"about_ca_system_score_gemma":0.00002117316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003640622,"about_ca_topic_score_gemma":0.0000087492,"domain_scores_codex":[0.996125,0.0006104714,0.0006038129,0.001121289,0.000780788,0.0007586314],"domain_scores_gemma":[0.9956337,0.00007697516,0.0002315764,0.003545265,0.0002807849,0.0002317108],"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":[0.000008311833,0.00007766009,4.11668e-7,0.0001742312,0.00002941793,0.00009153639,0.0001397018,0.0001164357,0.000003369693,0.0002659341,0.9919855,0.007107466],"study_design_scores_gemma":[0.0003670598,0.0001076313,0.00006349406,0.0001520455,0.000008717037,0.0001515072,0.00003806999,0.005774173,9.858766e-7,0.00006543312,0.9929131,0.0003577483],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001900708,0.0001202628,0.009736697,0.0004855531,0.001299215,0.0005060717,0.9833189,0.00137133,0.003142908],"genre_scores_gemma":[0.0002678761,0.0002191659,0.0001933007,0.0001280562,0.0004791389,5.563187e-8,0.9976891,0.0006759911,0.0003473227],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06907991,"threshold_uncertainty_score":0.9999021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07274279771675186,"score_gpt":0.275631684977588,"score_spread":0.2028888872608361,"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."}}