{"id":"W6969084981","doi":"10.5683/sp3/y5czvy","title":"Read_Me Gess 2006 Maillardville corpus Word List 1","year":2022,"lang":"en","type":"dataset","venue":"Borealis","topic":"History of Computing Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Word (group theory); Word list; Corpus linguistics; Word processing","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":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0005382207,0.0004859536,0.0006083216,0.0005306063,0.000471841,0.0002372161,0.00695417,0.0004128213,0.0008871215],"category_scores_gemma":[0.0003019658,0.0005201929,0.0001963867,0.0006392605,0.0002225568,0.0001660064,0.003259346,0.0009707837,0.00005534292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004769976,"about_ca_system_score_gemma":0.000327385,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02138115,"about_ca_topic_score_gemma":0.005007507,"domain_scores_codex":[0.9967695,0.0001706702,0.0004809504,0.001030492,0.0009076028,0.0006407502],"domain_scores_gemma":[0.9949081,0.0001760579,0.0004717057,0.004207217,0.0001033447,0.0001335773],"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":[0.000004390418,0.00005364688,0.000001919475,0.00004203948,0.00002812887,0.0003519844,0.00003175501,0.00002184502,0.000001356155,0.001401184,0.9897866,0.00827518],"study_design_scores_gemma":[0.0001521559,0.00009096478,0.00003076477,0.00003840849,0.00002455326,0.00009504841,0.000008881948,0.00008001979,0.00001290277,0.0008724814,0.9980139,0.0005799512],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000002945935,0.001104724,0.00157203,0.001152927,0.001704064,0.0002658653,0.9908782,0.001495598,0.001823678],"genre_scores_gemma":[0.000002407945,0.0003246908,0.006374378,0.0005720211,0.0001796755,0.00008177731,0.9916444,0.00003482459,0.0007858269],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01637365,"threshold_uncertainty_score":0.999725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01669748485992586,"score_gpt":0.2393405105893056,"score_spread":0.2226430257293797,"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."}}