{"id":"W4399203487","doi":"10.1080/10618600.2024.2362219","title":"Iterated Data Sharpening","year":2024,"lang":"en","type":"article","venue":"Journal of Computational and Graphical Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Sharpening; Computer science; Artificial intelligence; Mathematics; Algorithm","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006480122,0.00009534411,0.0002178893,0.0001150828,0.00006009582,0.0001633986,0.0001700183,0.00004164405,0.0001305139],"category_scores_gemma":[0.001590964,0.00006818346,0.00002797518,0.0002091742,0.0001025107,0.0001260263,0.00007357222,0.0002872812,0.000003086291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007873439,"about_ca_system_score_gemma":0.00007860599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001652376,"about_ca_topic_score_gemma":6.816026e-7,"domain_scores_codex":[0.9988062,0.00008698482,0.0005069373,0.0001378743,0.0003513765,0.000110595],"domain_scores_gemma":[0.9943489,0.005064075,0.0001145081,0.0000823465,0.0002642565,0.0001259549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002047919,0.00003351402,0.0001269117,0.0001110872,0.00007414934,0.0001481733,0.00006337673,0.00004088159,0.00001299843,0.9317748,0.01189882,0.05569483],"study_design_scores_gemma":[0.0001361535,0.0001091951,0.002409313,0.0001268527,0.00006016116,0.000206369,0.000009743392,0.1664907,0.000001823063,0.8280997,0.002276737,0.00007322897],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008064119,0.0004660868,0.9899573,0.0005123142,0.000244499,0.00003525673,0.0005860891,0.00001541869,0.00011892],"genre_scores_gemma":[0.2194468,0.00004798284,0.780205,0.00009702338,0.0001393571,3.588574e-7,0.00003091508,0.000009510051,0.0000230074],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2113827,"threshold_uncertainty_score":0.2780441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1454890845383303,"score_gpt":0.4105353640326388,"score_spread":0.2650462794943085,"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."}}