{"id":"W2981183195","doi":"10.48550/arxiv.1910.08857","title":"LRP2020: Astrostatistics in Canada","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Training (meteorology); White paper; Norm (philosophy); Statistical analysis; Professional development; Political science; Library science; Psychology; Medical education; Public relations; Geography; Computer science; Pedagogy; Statistics; Engineering; Mathematics; Medicine; Meteorology","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":[0.011616,0.002191718,0.001691535,0.01157883,0.00508902,0.01076827,0.005455222,0.003665563,0.1379621],"category_scores_gemma":[0.01885526,0.001025725,0.001119692,0.02499935,0.002664925,0.004043236,0.003695087,0.003438926,0.08966164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0616882,"about_ca_system_score_gemma":0.2389172,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9517767,"about_ca_topic_score_gemma":0.9259374,"domain_scores_codex":[0.9901682,0.0004605212,0.0004506975,0.0007972029,0.006390993,0.001732377],"domain_scores_gemma":[0.9469275,0.002278659,0.001247182,0.001465839,0.03695956,0.01112135],"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":[0.00001524746,0.0000068719,0.0002605373,0.0000787218,0.000002468668,0.00001282592,0.00001521652,0.0001142926,0.00003781615,0.001782869,0.9861647,0.01150857],"study_design_scores_gemma":[0.000009707007,0.000008711003,0.002969031,0.0001331863,0.0000029893,0.00001106549,0.00003981129,0.000170737,0.00006595422,0.0004083925,0.9961632,0.00001718238],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.002692426,0.0413094,0.005398422,0.08952452,0.0528752,0.00124893,0.330705,0.01605649,0.4601896],"genre_scores_gemma":[0.02150404,0.03918923,0.008664183,0.01883187,0.01026377,0.0009664714,0.2353226,0.006206923,0.6590509],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1379621,"threshold_uncertainty_score":0.4615294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04302887935181211,"score_gpt":0.1593758620482718,"score_spread":0.1163469826964597,"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."}}