{"id":"W3116307283","doi":"","title":"Prose and cons of scholarly articles: How readability tests expose poor knowledge mobilization in academic publications","year":2021,"lang":"en","type":"article","venue":"Journal of Professional Communication","topic":"Text Readability and Simplification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Readability; Reading (process); Comprehension; Meaning (existential); Index (typography); Psychology; Reading comprehension; Social science; Sociology; Political science; Computer science; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01808631,0.0004645849,0.0005894984,0.007957153,0.0008297046,0.005422721,0.000653118,0.001087493,0.003743249],"category_scores_gemma":[0.2358716,0.0002224089,0.0008498443,0.00411636,0.002043199,0.005119059,0.003074193,0.001020315,0.0008007365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008827347,"about_ca_system_score_gemma":0.0008052679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006057904,"about_ca_topic_score_gemma":0.0007789187,"domain_scores_codex":[0.9733279,0.009185025,0.004787692,0.001523733,0.01052606,0.0006495197],"domain_scores_gemma":[0.6174892,0.277058,0.07242586,0.008971338,0.02058383,0.003471848],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001256328,0.0003225874,0.8364581,0.0009425618,0.0006137065,0.0007607663,0.02823755,0.0004779966,0.003067611,0.001935438,0.00236945,0.1235579],"study_design_scores_gemma":[0.00003587905,0.0006584824,0.955274,0.0006902706,0.0003163696,0.002059906,0.02390396,0.001680807,0.003406855,0.006332506,0.005498152,0.0001428767],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9874842,0.001253108,0.001657559,0.0006856968,0.00008379132,0.00008763211,0.0003308302,0.00005995588,0.00835725],"genre_scores_gemma":[0.9969878,0.0003205468,0.001257201,0.000122312,0.00008277172,0.00007790425,0.0002479939,0.00003957106,0.0008638751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9945773,"threshold_uncertainty_score":0.09565061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08257423262281025,"score_gpt":0.3646460487182441,"score_spread":0.2820718160954339,"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."}}