{"id":"W3082898239","doi":"","title":"Can language help in the characterization of user behavior? Feature engineering experiments with Word.","year":2020,"lang":"en","type":"article","venue":"Software Engineering and Knowledge Engineering","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Word (group theory); Natural language processing; Feature (linguistics); Feature engineering; Characterization (materials science); Artificial intelligence; Linguistics","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":[0.00507036,0.000512571,0.0004035585,0.0005648502,0.0003829486,0.00190454,0.0005522162,0.0010326,0.003818965],"category_scores_gemma":[0.06935865,0.0003729629,0.0002777358,0.0003533615,0.0007104963,0.003752038,0.0008662587,0.0009834048,0.001085453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000238872,"about_ca_system_score_gemma":0.0003262376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001223334,"about_ca_topic_score_gemma":0.0008285354,"domain_scores_codex":[0.9955759,0.002972037,0.0003097575,0.0005613878,0.000419898,0.0001609688],"domain_scores_gemma":[0.9123138,0.07944104,0.002336245,0.003126326,0.001657977,0.001124701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.03585144,0.008690902,0.1068836,0.002324898,0.0003417649,0.0007672694,0.04692393,0.004352037,0.249981,0.005256701,0.005121233,0.5335051],"study_design_scores_gemma":[0.002851798,0.05110092,0.5966911,0.0006801397,0.001679384,0.002923719,0.0310218,0.1308094,0.1239072,0.0350789,0.02256962,0.0006861106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900421,0.0002218829,0.006628239,0.0001835076,0.00004423099,0.000119783,0.0001690463,0.0001981902,0.002393069],"genre_scores_gemma":[0.9929678,0.00009457468,0.005042937,0.0001189012,0.00001524563,0.0001239862,0.0001501201,0.0001038376,0.001382629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00507036,"threshold_uncertainty_score":0.02681494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008040751016663957,"score_gpt":0.2017774018925776,"score_spread":0.1937366508759136,"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."}}