{"id":"W6989531529","doi":"","title":"Automatic Recognition of Text Difficulty from Consumer Health Information","year":2006,"lang":"en","type":"article","venue":"NPARC","topic":"Health Literacy and Information Accessibility","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Readability; Reading (process); Feature (linguistics); Word (group theory); The Internet; Support vector machine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005914898,0.0006382345,0.000561706,0.00397438,0.00018793,0.0008961137,0.0003499255,0.0007156224,0.003093172],"category_scores_gemma":[0.007198387,0.0001551568,0.0003574319,0.001565314,0.0001779929,0.001169086,0.0005163458,0.0005053258,0.001612294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002787468,"about_ca_system_score_gemma":0.0002160182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001329817,"about_ca_topic_score_gemma":0.00130632,"domain_scores_codex":[0.9993975,0.0001202364,0.00008348207,0.0001453812,0.0001949126,0.00005846074],"domain_scores_gemma":[0.9940124,0.003079681,0.0008918766,0.000303205,0.001509853,0.0002029613],"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":[0.001583996,0.0005965133,0.2382454,0.0007504582,0.0001512069,0.000912031,0.000699954,0.002133645,0.08008501,0.0005107244,0.009154959,0.6651762],"study_design_scores_gemma":[0.00009114217,0.0007462116,0.7772598,0.00007686616,0.0001273435,0.002190983,0.0008367301,0.1752036,0.03612414,0.001817844,0.005437572,0.00008774156],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9569286,0.000426386,0.03342967,0.0002104059,0.00005515643,0.000299323,0.003394009,0.001617847,0.003638659],"genre_scores_gemma":[0.9482101,0.0002221954,0.04215486,0.00005284417,0.0000979153,0.000227908,0.006811624,0.00008040265,0.002142177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00397438,"threshold_uncertainty_score":0.01034772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04057809473964964,"score_gpt":0.3831720933619724,"score_spread":0.3425939986223228,"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."}}