{"id":"W4394380841","doi":"10.6084/m9.figshare.6813131","title":"Machine learning databases used for Journal of Geophysical Research: Space Physics manuscript: \"New capabilities for prediction of high-latitude ionospheric scintillation: A novel approach with machine learning.\"","year":2018,"lang":"en","type":"dataset","venue":"Figshare","topic":"Earthquake Detection and Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Ionosphere; Space (punctuation); Space weather; Scintillation; High latitude; Computer science; Database; Latitude; Geophysics; Physics; Astronomy; Telecommunications","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":[0.001202455,0.002235624,0.001363399,0.003114033,0.0008466706,0.002056802,0.003541395,0.001883173,0.05058187],"category_scores_gemma":[0.007732732,0.0006240865,0.001474593,0.007122329,0.0004616747,0.001923419,0.00200646,0.002799683,0.08121207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00148076,"about_ca_system_score_gemma":0.002359407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01643282,"about_ca_topic_score_gemma":0.02036444,"domain_scores_codex":[0.9984306,0.0001743409,0.0002717483,0.0004422397,0.0004864312,0.0001947157],"domain_scores_gemma":[0.996453,0.0007548126,0.0003272036,0.001129756,0.001072817,0.0002623561],"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":[0.00007120965,0.0000321129,0.0009143937,0.0003462409,0.00003302329,0.0000226157,0.00001506993,0.0006077351,0.0001375131,0.0003941881,0.9940619,0.003364058],"study_design_scores_gemma":[0.0003027319,0.0000326904,0.00664782,0.0002277519,0.00003601408,0.00008558674,0.00009941965,0.002624984,0.001561942,0.002257412,0.9860723,0.00005129299],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002084604,0.00002933298,0.0001780114,0.00007034672,0.00004822324,0.00001913722,0.997951,0.0009595277,0.0005361107],"genre_scores_gemma":[0.0005187971,0.00002585783,0.0004713167,0.00003527945,0.000007360954,0.00007131736,0.9983436,0.0001004064,0.0004261103],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05058187,"threshold_uncertainty_score":0.1692132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.111673611253554,"score_gpt":0.2809746145648109,"score_spread":0.1693010033112569,"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."}}