{"id":"W2925077947","doi":"10.1371/journal.pone.0212342","title":"Talk2Me: Automated linguistic data collection for personal assessment","year":2019,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Vector Institute; St. Michael's Hospital; University of Toronto; Carleton University","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Alzheimer Society Research Program; Alzheimer Society; California HIV/AIDS Research Program","keywords":"Computer science; Variety (cybernetics); Natural language processing; Software; Artificial intelligence; Baseline (sea); Linguistics; Programming language","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004619128,0.001654793,0.0009973162,0.005407118,0.0007442786,0.001899989,0.001604873,0.001056228,0.03492023],"category_scores_gemma":[0.02459186,0.0007678864,0.0008719313,0.001969941,0.0004509206,0.002353273,0.004890538,0.001355392,0.02671683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004985121,"about_ca_system_score_gemma":0.001798652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003060543,"about_ca_topic_score_gemma":0.007360207,"domain_scores_codex":[0.9956639,0.001525549,0.0004892703,0.0008984103,0.001217444,0.0002053866],"domain_scores_gemma":[0.9839789,0.006136079,0.001091415,0.003391322,0.004216948,0.00118531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002364023,0.0008111137,0.0474245,0.002271766,0.0004970247,0.0005726962,0.002190866,0.002315152,0.02406579,0.002406662,0.3493814,0.565699],"study_design_scores_gemma":[0.000947936,0.001573181,0.3680009,0.001029355,0.0003525508,0.003134979,0.002869547,0.06367804,0.07585905,0.02578681,0.4558626,0.0009050398],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.121406,0.0009188131,0.2836477,0.0009930739,0.0005816424,0.005517691,0.3957501,0.1631154,0.02806969],"genre_scores_gemma":[0.1932817,0.0005348311,0.3846285,0.0007414257,0.0003986695,0.01288809,0.3763373,0.008563276,0.02262617],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03492023,"threshold_uncertainty_score":0.1168199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05615982920436336,"score_gpt":0.3195040284921692,"score_spread":0.2633441992878059,"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."}}