{"id":"W4296185672","doi":"10.1029/2022gl100912","title":"A 2D Kaleidoscope of Electron Heat Fluxes Driven by Auroral Electron Precipitation","year":2022,"lang":"en","type":"article","venue":"Geophysical Research Letters","topic":"Ionosphere and magnetosphere dynamics","field":"Physics and Astronomy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Electron precipitation; Substorm; Electron; Precipitation; Ionosphere; Physics; Atmospheric sciences; Flux (metallurgy); Computational physics; Heat flux; Kinetic energy; Geophysics; Environmental science; Meteorology; Magnetosphere; Plasma; Materials science; Heat transfer; Mechanics; Nuclear physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001603404,0.0003516023,0.0002884791,0.0007563172,0.0003069545,0.0005983781,0.0003769865,0.0003087696,0.008670692],"category_scores_gemma":[0.0004544627,0.0002555092,0.0004038438,0.00055322,0.00013369,0.0004035977,0.0003488634,0.0004079793,0.0009486285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002692824,"about_ca_system_score_gemma":0.0003405072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005468302,"about_ca_topic_score_gemma":0.006938148,"domain_scores_codex":[0.9999366,0.000006985073,0.000004479356,0.00002115964,0.00002284959,0.000007863481],"domain_scores_gemma":[0.9998517,0.00003595887,0.00001190945,0.00003241847,0.00005296884,0.00001510778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0006585001,0.0002486602,0.04093554,0.000378904,0.0002546748,0.00117661,0.0007020134,0.5358616,0.2302349,0.01362563,0.03626302,0.1396599],"study_design_scores_gemma":[0.00004560508,0.00002228109,0.0173843,0.00001436808,0.00001259,0.0001161296,0.00006268367,0.9547826,0.01275952,0.001982479,0.01277717,0.00004027264],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2927768,0.0001811588,0.6424767,0.0002015356,0.0002593575,0.0002879485,0.02324915,0.01687485,0.02369258],"genre_scores_gemma":[0.8153203,0.0001738356,0.1709673,0.00007291711,0.00005046338,0.0002134242,0.007841209,0.001102055,0.00425851],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008670692,"threshold_uncertainty_score":0.02900636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00972580838995163,"score_gpt":0.2820890574062547,"score_spread":0.272363249016303,"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."}}