{"id":"W4229552440","doi":"10.17161/iallt.v17i2.9154","title":"NALLD Membership Roster","year":2019,"lang":"en","type":"article","venue":"IALLT Journal of Language Learning Technologies","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Concordia University; University of Alberta; York University; University of St Andrews; Boston College; University of South Dakota; Turun Yliopisto; University of Oxford; University of Windsor; Texas State University; University of Minnesota; Simon Fraser University; McGill University; Fukuoka University; University of Lethbridge; Helsingin Yliopisto; Escuela Superior Politécnica del Litoral; Nanzan University; University of Pittsburgh","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0009785654,0.001000473,0.0009242715,0.001932922,0.001669405,0.004832454,0.001502006,0.002763063,0.9102932],"category_scores_gemma":[0.002961826,0.0003567082,0.0007224232,0.001061792,0.0004185878,0.002110419,0.00417278,0.001486011,0.8952966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009032385,"about_ca_system_score_gemma":0.002328051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001846137,"about_ca_topic_score_gemma":0.003884268,"domain_scores_codex":[0.9992127,0.00006978515,0.00003681033,0.0001710667,0.0003528409,0.0001567451],"domain_scores_gemma":[0.9979081,0.0001509041,0.00008898969,0.0002660329,0.0005579633,0.001028096],"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":[0.00009935272,0.00007548818,0.00017021,0.0001036231,0.000003966627,0.00005191771,0.00002153055,0.00006413739,0.0003847668,0.002117355,0.8892699,0.1076376],"study_design_scores_gemma":[0.00001340477,0.00001910142,0.0002500735,0.00005269774,0.000002419481,0.00002944797,0.00002409399,0.0000716601,0.0001087581,0.0005999941,0.9988247,0.000003836297],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"dataset","genre_scores_codex":[0.0006788239,0.0007335689,0.0007909408,0.003332209,0.005251889,0.0001291917,0.005113294,0.001678533,0.9822916],"genre_scores_gemma":[0.0009504608,0.0001823065,0.0002396358,0.0003238808,0.0002406768,0.00003468174,0.001358247,0.0002348758,0.9964352],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.9102932,"threshold_uncertainty_score":0.1279559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0223029227099266,"score_gpt":0.2126312296838425,"score_spread":0.1903283069739159,"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."}}