{"id":"W4299335947","doi":"10.1007/978-3-031-01880-0_3","title":"Mining Text Conversations","year":2011,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on data management","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Natural language processing; Linguistics; Philosophy","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":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.0003674279,0.0005411314,0.0004976907,0.0007394264,0.0001865683,0.0002203998,0.006129147,0.0002044365,0.0007580015],"category_scores_gemma":[0.00008460427,0.0005071689,0.0001630898,0.00011601,0.0001000168,0.0005436626,0.003131927,0.000289222,0.0006318128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001422046,"about_ca_system_score_gemma":0.00003041782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001151833,"about_ca_topic_score_gemma":0.00004484983,"domain_scores_codex":[0.9969881,0.00004284989,0.000444595,0.001541095,0.000627283,0.0003561256],"domain_scores_gemma":[0.9927807,0.0002908452,0.0003949958,0.006381474,0.00005414557,0.00009786022],"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":[0.000005204965,0.00002446475,5.916217e-7,0.00003573364,0.0004464709,0.00006093699,0.00004060881,0.00001018941,0.000001422368,0.5682161,0.04826719,0.382891],"study_design_scores_gemma":[0.00007258885,0.00003742054,0.0000136466,0.0002705998,0.000333761,0.000002163046,0.000006483511,0.0006101051,0.0004174864,0.08014992,0.9174407,0.0006451264],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[1.953938e-7,0.0001905174,0.3747708,0.0003518469,0.0001182855,0.0003218624,0.00005891706,0.0004751363,0.6237124],"genre_scores_gemma":[0.01026086,0.002710593,0.4653215,0.003013917,0.000315481,0.0002328927,0.0006348258,0.000263073,0.5172468],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8691735,"threshold_uncertainty_score":0.999738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0607115427774878,"score_gpt":0.2734736238599594,"score_spread":0.2127620810824716,"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."}}