{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002506541,0.0005137993,0.0002662688,0.005386691,0.001288318,0.001800149,0.0003729012,0.0006852373,0.003038725],"category_scores_gemma":[0.02119268,0.0001952012,0.00033361,0.004757015,0.0007458573,0.002637121,0.001103059,0.0007798572,0.001118676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009554988,"about_ca_system_score_gemma":0.0009360603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002463988,"about_ca_topic_score_gemma":0.00552275,"domain_scores_codex":[0.9972879,0.001301777,0.0002632643,0.0004939753,0.0005341292,0.0001190182],"domain_scores_gemma":[0.9671417,0.02517189,0.00372078,0.0009911134,0.002634546,0.0003398663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002431288,0.0004582211,0.2008424,0.006525504,0.0002041517,0.002817826,0.1754769,0.003737464,0.1152229,0.02781128,0.0302577,0.4342143],"study_design_scores_gemma":[0.0001406319,0.0005028408,0.5073072,0.001925204,0.0002716814,0.001929442,0.09359064,0.04230954,0.03756946,0.02942623,0.2847615,0.0002655852],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9277201,0.002384705,0.03940231,0.0008241249,0.0001970798,0.0006578077,0.01447532,0.0007033015,0.01363534],"genre_scores_gemma":[0.9268479,0.0006576861,0.04726352,0.00009935007,0.0001129966,0.0008345289,0.02074926,0.0001520083,0.003282733],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005386691,"threshold_uncertainty_score":0.01325601,"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."}}