{"id":"W2767644820","doi":"10.1080/02687038.2017.1398811","title":"Discourse measurement in aphasia research: have we reached the tipping point? A core outcome set … or greater standardisation of discourse measures?","year":2017,"lang":"en","type":"article","venue":"Aphasiology","topic":"Delphi Technique in Research","field":"Social Sciences","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Aphasia; Outcome (game theory); Set (abstract data type); Tipping point (physics); Core (optical fiber); Psychology; Point (geometry); Rehabilitation; Linguistics; Cognitive psychology; Epistemology; Computer science; Philosophy; Economics; Neuroscience; Engineering; Mathematics","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.6965732,0.001662152,0.00600636,0.009339195,0.006241519,0.01880751,0.009634516,0.008619911,0.002402878],"category_scores_gemma":[0.7043707,0.001526671,0.00277067,0.006667288,0.03382516,0.04525615,0.01883958,0.02418399,0.001114532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01506408,"about_ca_system_score_gemma":0.02866283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006437487,"about_ca_topic_score_gemma":0.004631131,"domain_scores_codex":[0.4335826,0.4427615,0.04952916,0.01245229,0.05837315,0.003301341],"domain_scores_gemma":[0.228213,0.5863984,0.03080893,0.04478473,0.1039107,0.005884374],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006561421,0.0003478967,0.01278565,0.01627196,0.0007141213,0.0001013237,0.04481103,0.0005220494,0.001501538,0.2018555,0.02399662,0.6964362],"study_design_scores_gemma":[0.0005125504,0.003195145,0.03985516,0.05475565,0.0007853835,0.000951553,0.05478821,0.007213511,0.007489234,0.6789709,0.150389,0.001093656],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.02777704,0.1043315,0.2153548,0.6164367,0.02093292,0.002021193,0.0003393746,0.0005407653,0.01226571],"genre_scores_gemma":[0.4418725,0.04296042,0.4012516,0.09051389,0.009379389,0.01070711,0.0006437995,0.000614313,0.002056915],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.3034268,"threshold_uncertainty_score":0.3741793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8161757676509586,"score_gpt":0.6240066150962641,"score_spread":0.1921691525546945,"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."}}