{"id":"W3210533271","doi":"10.5281/zenodo.3978643","title":"SuperDARN/pydarn: pyDARN v1.1.0 Release","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Mathematics, Computing, and Information Processing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005571975,0.0001587873,0.0001688961,0.000148857,0.001880593,0.001922005,0.002165873,0.00005347028,0.004048273],"category_scores_gemma":[0.0009569299,0.0001644896,0.00006175749,0.000781219,0.00009009526,0.001147975,0.001819731,0.0002845028,0.01190794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006405017,"about_ca_system_score_gemma":0.00001097287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003030932,"about_ca_topic_score_gemma":2.647795e-8,"domain_scores_codex":[0.9981583,0.0001598226,0.000403862,0.0004055239,0.000494682,0.0003777697],"domain_scores_gemma":[0.9984062,0.00002723569,0.0001751109,0.0005116166,0.0005518904,0.0003279554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002298715,0.0001354019,0.00000392781,0.0004040886,0.00003865688,0.0000256995,0.0217647,0.0003965099,0.001211326,0.109397,0.4248088,0.4417909],"study_design_scores_gemma":[0.0003545774,0.0001168341,0.00003788413,0.00003177559,0.000004554639,0.00006687086,0.00027943,0.1032511,0.0006989638,0.0007920196,0.8941516,0.0002144091],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003226251,0.00007271896,0.7737935,0.004809732,0.0001325358,0.000287752,0.00002159691,0.002224075,0.2154318],"genre_scores_gemma":[0.9717267,0.00005558413,0.02114483,0.004196613,0.0004260615,5.662245e-8,0.0003365804,0.0009852529,0.001128315],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9685004,"threshold_uncertainty_score":0.9994188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04212632270358025,"score_gpt":0.2318143176604567,"score_spread":0.1896879949568764,"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."}}