{"id":"W2803063809","doi":"10.1075/itl.00009.sas","title":"The guessing from context test","year":2018,"lang":"en","type":"article","venue":"ITL Review of Applied Linguistics","topic":"Second Language Acquisition and Learning","field":"Psychology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Rasch model; Representativeness heuristic; Context (archaeology); Test (biology); Meaning (existential); Construct validity; Psychology; Interpretation (philosophy); Construct (python library); Natural language processing; Item response theory; Test validity; Linguistics; Cognitive psychology; Social psychology; Psychometrics; Computer science; Developmental psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003116082,0.0006773753,0.0008578222,0.002139969,0.0006485955,0.001439003,0.0009275997,0.001099075,0.007612221],"category_scores_gemma":[0.03276308,0.0002021855,0.0009885908,0.0008562767,0.001030228,0.002542504,0.001693511,0.001194986,0.001801874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005227904,"about_ca_system_score_gemma":0.0008608645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001513652,"about_ca_topic_score_gemma":0.001776126,"domain_scores_codex":[0.9965693,0.001266568,0.0005105439,0.0004899451,0.0009256807,0.0002379851],"domain_scores_gemma":[0.9815029,0.008795148,0.002906468,0.001814052,0.003504315,0.001477063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001719091,0.001117175,0.7029455,0.0006575109,0.000296224,0.001166368,0.005609377,0.002959546,0.008053059,0.006752444,0.005520381,0.2632033],"study_design_scores_gemma":[0.0002628216,0.004985764,0.9043643,0.0007328623,0.0002653629,0.003849611,0.008733356,0.01939296,0.01715984,0.01749489,0.02248508,0.0002730907],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9734035,0.0005541635,0.00766127,0.0002914833,0.0001338881,0.0007027619,0.0008406412,0.0001564049,0.01625591],"genre_scores_gemma":[0.9887222,0.0002134739,0.007084506,0.0001403291,0.00002886538,0.0004521209,0.0008503883,0.00002178626,0.002486244],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007612221,"threshold_uncertainty_score":0.02546543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01822440155309714,"score_gpt":0.3379645676489276,"score_spread":0.3197401660958304,"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."}}