{"id":"W7095566492","doi":"","title":"On behalf of TESL Ontario we thank the Ministry of Education, the Ministry of Citizenship and Im- migration and the Ministry of Train-","year":2015,"lang":"en","type":"article","venue":"","topic":"Multilingual Education and Policy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Christian ministry; Citizenship; Settlement (finance); Reading (process); Event (particle 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001545391,0.0004688891,0.0004728912,0.001034422,0.008241755,0.003812711,0.0006907508,0.00117984,0.1873063],"category_scores_gemma":[0.004320399,0.0003120057,0.0001833354,0.001677091,0.001318331,0.001109811,0.001998829,0.002459474,0.04007892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01585862,"about_ca_system_score_gemma":0.05111473,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6557658,"about_ca_topic_score_gemma":0.9000425,"domain_scores_codex":[0.9982766,0.000175336,0.00005925827,0.0001826763,0.0009163119,0.0003897612],"domain_scores_gemma":[0.9893852,0.0006392376,0.0004876825,0.0003266177,0.005158786,0.004002572],"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":[0.00008534067,0.00001510634,0.002088401,0.00009962256,0.000003650055,0.000250463,0.001697344,0.00002978988,0.0007774497,0.003377461,0.9713106,0.02026483],"study_design_scores_gemma":[0.00000357518,0.000005113937,0.002224839,0.0000222715,0.000001571477,0.00003152482,0.001787933,0.00003922363,0.0001098471,0.00008173112,0.9956867,0.000005703474],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01706554,0.005185514,0.001372597,0.2537425,0.01315992,0.0004272541,0.01208865,0.0009774177,0.6959806],"genre_scores_gemma":[0.02058688,0.0009044399,0.0006644231,0.004573489,0.0003521995,0.00007595494,0.001055496,0.0002269556,0.9715602],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8126937,"threshold_uncertainty_score":0.6925229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08899778931901092,"score_gpt":0.4132481832029894,"score_spread":0.3242503938839785,"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."}}