{"id":"W4404906996","doi":"10.1386/public_00225_1","title":"A Machine to Listen to the Sky: Transducing Space Weather","year":2024,"lang":"en","type":"article","venue":"Public","topic":"Space exploration and regulation","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Sky; Space weather; Space (punctuation); Meteorology; Computer science; Geography; Operating system","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":[],"consensus_categories":[],"category_scores_codex":[0.0001220287,0.0000654239,0.00005243371,0.00006893672,0.00007653642,0.0002711674,0.00008812578,0.00001152946,0.0008397215],"category_scores_gemma":[0.00000380377,0.00004100832,0.00004800488,0.0003547802,0.000005570315,0.000127848,0.00001870363,0.00006135451,0.0006646134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001401166,"about_ca_system_score_gemma":0.00002710958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009576654,"about_ca_topic_score_gemma":0.00005049896,"domain_scores_codex":[0.9995548,0.00001989406,0.00006574135,0.0001386949,0.00009490837,0.0001259474],"domain_scores_gemma":[0.9997279,0.00001734964,0.000007765909,0.0001460482,0.0000219583,0.00007896801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008547267,0.00005884105,0.003306908,0.00001278318,0.0001017265,9.836407e-7,0.01467056,0.001395097,0.002406098,0.6544909,0.07427747,0.2492701],"study_design_scores_gemma":[0.00005921679,0.00001379547,0.001498442,0.00001279725,0.00000697627,3.049324e-7,0.0005463174,0.004420226,0.000255339,0.0007233873,0.9923847,0.00007851967],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.06285101,0.0003068054,0.2480559,0.6127188,0.001053715,0.0006426206,0.0000358184,0.0002324372,0.07410289],"genre_scores_gemma":[0.9845631,4.03198e-7,0.0002594852,0.0004198401,0.0005591084,0.00004847077,0.00001705815,0.00001473488,0.01411781],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9217121,"threshold_uncertainty_score":0.9194362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01678921781701646,"score_gpt":0.2555729346388496,"score_spread":0.2387837168218332,"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."}}