{"id":"W2397437854","doi":"","title":"Speech Acts, Dialogues and the Common Ground.","year":2012,"lang":"en","type":"article","venue":"The Florida AI Research Society","topic":"Rhetoric and Communication Studies","field":"Arts and Humanities","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Collège de Maisonneuve","funders":"","keywords":"Common ground; Computer science; Speech recognition; Communication; Sociology","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":["sts"],"consensus_categories":["sts"],"category_scores_codex":[0.003513291,0.00009853364,0.0001574842,0.0000127824,0.00315033,0.000324724,0.0005271799,0.00003171449,0.0001575394],"category_scores_gemma":[0.00008707977,0.00004512797,0.000111662,0.00007618351,0.002909034,0.0002540635,0.0006174585,0.0006168273,0.0001380581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004336131,"about_ca_system_score_gemma":0.00002169908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001099039,"about_ca_topic_score_gemma":0.0002141496,"domain_scores_codex":[0.9983216,0.0005444112,0.0001429912,0.00009503811,0.0004712807,0.0004246738],"domain_scores_gemma":[0.99762,0.001550103,0.00003603002,0.0005437043,0.0001918722,0.00005831576],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002957625,0.00002914896,0.0005264133,0.00001180884,0.0001025686,9.692576e-8,0.2193718,6.91096e-8,0.000004891546,0.5865163,0.1909766,0.002430731],"study_design_scores_gemma":[0.000333946,0.00001825976,0.002097744,0.000007778377,0.00001545674,0.000001782369,0.06306231,0.0000339653,0.0000130367,0.01156627,0.9227768,0.0000726951],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4348951,0.04714173,0.00003448808,0.1166943,0.002131514,0.001493804,0.00003839883,0.0002352164,0.3973354],"genre_scores_gemma":[0.9757986,0.006234074,0.00001562112,0.001080796,0.002267115,0.0000964539,0.000004839233,0.0000119706,0.01449054],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7318001,"threshold_uncertainty_score":0.9998045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2030177407554121,"score_gpt":0.3669949231965671,"score_spread":0.163977182441155,"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."}}