{"id":"W2757021967","doi":"10.1002/asi.23882","title":"Discourse relations in rationale‐containing text‐segments","year":2017,"lang":"en","type":"article","venue":"Journal of the Association for Information Science and Technology","topic":"Topic Modeling","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Generalizability theory; Computer science; Leverage (statistics); Perspective (graphical); Sample (material); Face (sociological concept); Empirical research; Discourse analysis; Face-to-face interaction; Data science; Artificial intelligence; Linguistics; Sociology; Psychology; Epistemology; Communication","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002393716,0.00003804827,0.00007973515,0.0004527018,0.0007038563,0.0003667285,0.001067539,0.00005765481,4.366507e-7],"category_scores_gemma":[0.00412902,0.00002745111,0.00002403873,0.0003782461,0.00009654416,0.00638874,0.0002027246,0.0001321358,0.000002202645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002633953,"about_ca_system_score_gemma":0.0002916573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000313644,"about_ca_topic_score_gemma":0.000008277015,"domain_scores_codex":[0.9990399,0.000009296845,0.0003470242,0.00005691142,0.0004225924,0.0001242966],"domain_scores_gemma":[0.9977276,0.0000629252,0.001207635,0.0002420899,0.000738966,0.00002076699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000004869461,0.00001712071,0.2072882,0.000003958333,0.00001138289,2.186871e-7,0.001908485,0.0006823018,0.0003582631,0.717374,0.0003188404,0.07203238],"study_design_scores_gemma":[0.003827966,0.0002270899,0.5019058,0.0001600648,0.00002693529,0.00006665931,0.002939998,0.2548103,0.003024264,0.2070366,0.02565205,0.0003222384],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.648642,0.00003675765,0.2251069,0.1182386,0.001638231,0.0005089981,0.000003994826,0.00003663311,0.00578787],"genre_scores_gemma":[0.9932017,0.000005954299,0.006529455,0.0001418159,0.00001709801,0.000005016685,1.286277e-7,7.433821e-7,0.00009809116],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5103374,"threshold_uncertainty_score":0.5413564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01801076566800524,"score_gpt":0.2963604448376717,"score_spread":0.2783496791696665,"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."}}