{"id":"W4313596850","doi":"10.24256/ideas.v10i2.3136","title":"Speech Act Used by Main Character “Teddy” in The Man from Toronto Movie","year":2022,"lang":"en","type":"article","venue":"IDEAS Journal on English Language Teaching and Learning Linguistics and Literature","topic":"Language Acquisition and Education","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Character (mathematics); Speech act; Linguistics; Computer science; Directive; Psychology; Philosophy","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":[],"consensus_categories":[],"category_scores_codex":[0.0004754426,0.0003526381,0.000241343,0.0007084463,0.002403998,0.001159559,0.000279778,0.0005663653,0.002122291],"category_scores_gemma":[0.001938128,0.0001380674,0.0001412902,0.0006098174,0.002002675,0.0005750522,0.0007147085,0.0006489804,0.0004084132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004159267,"about_ca_system_score_gemma":0.001201898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1403373,"about_ca_topic_score_gemma":0.3140011,"domain_scores_codex":[0.9993286,0.0003560859,0.00003025394,0.00006664521,0.0001247271,0.00009374938],"domain_scores_gemma":[0.9987352,0.0005865015,0.0001919323,0.00005147219,0.000241748,0.0001932219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001930994,0.00002824491,0.03508673,0.0002513984,0.00001601522,0.003123416,0.9237775,0.0001465737,0.01904416,0.002724027,0.004085556,0.01152337],"study_design_scores_gemma":[0.000007105405,0.0001836795,0.1552854,0.0001866991,0.00003549855,0.002638209,0.7643157,0.0005676956,0.007233634,0.0001766659,0.06925765,0.0001122215],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855821,0.0006225132,0.001174336,0.0006244504,0.00006909086,0.00006136945,0.0004692711,0.00003456802,0.01136234],"genre_scores_gemma":[0.9910558,0.0004709056,0.0008391923,0.0001542372,0.00001375381,0.00003983552,0.0002433145,0.00001582503,0.007167065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1403373,"threshold_uncertainty_score":0.279041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00578787557799235,"score_gpt":0.2815713600275128,"score_spread":0.2757834844495204,"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."}}