{"id":"W3016700105","doi":"10.1075/slsi.33.03tal","title":"Mobilizing for the next relevant action","year":2020,"lang":"en","type":"book-chapter","venue":"Studies in language and social interaction","topic":"Language, Discourse, Communication Strategies","field":"Arts and Humanities","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Action (physics); Computer science; Political science; Physics","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":[0.0007609864,0.0006648546,0.0002717957,0.000749083,0.001133475,0.003368914,0.0009609345,0.0009098003,0.02025237],"category_scores_gemma":[0.001617514,0.0001740748,0.0004601528,0.0002958228,0.002159651,0.00289312,0.003272578,0.00133528,0.004409674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006717543,"about_ca_system_score_gemma":0.0008464532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001132266,"about_ca_topic_score_gemma":0.001623285,"domain_scores_codex":[0.9992591,0.0002964176,0.00002227391,0.0001356673,0.0001841136,0.0001023525],"domain_scores_gemma":[0.9994888,0.0002713422,0.00002872152,0.00005564987,0.00006207292,0.00009333066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002498097,0.0002068171,0.002076973,0.000555847,0.00002561062,0.001723001,0.1227999,0.001057687,0.0475087,0.5676733,0.01584044,0.240282],"study_design_scores_gemma":[0.00003789413,0.0002618261,0.003270942,0.001319664,0.00005791086,0.001559371,0.05973481,0.004032281,0.01944394,0.06863178,0.841559,0.0000904972],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.089563,0.002094027,0.06675678,0.002408506,0.0004544716,0.0001875953,0.0001255021,0.0008117916,0.8375983],"genre_scores_gemma":[0.7859478,0.002133837,0.03047883,0.0005109613,0.0001238636,0.0002065864,0.0002989582,0.0003891001,0.1799101],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02025237,"threshold_uncertainty_score":0.06775093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3088915940543575,"score_gpt":0.4210659381320367,"score_spread":0.1121743440776792,"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."}}