{"id":"W2903461828","doi":"","title":"Intelligent and Affectively Aligned Evaluation of Online Health Information for Older Adults.","year":2017,"lang":"en","type":"article","venue":"National Conference on Artificial Intelligence","topic":"Health Literacy and Information Accessibility","field":"Health Professions","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; University of British Columbia","funders":"","keywords":"Computer science; Human–computer interaction; Data science; World Wide Web; Internet privacy","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":[0.002020804,0.0002476431,0.0002590239,0.0004453347,0.0002767868,0.0009387567,0.0002545422,0.0005075374,0.004390043],"category_scores_gemma":[0.01681613,0.00009793042,0.0002292967,0.0001884811,0.0001378128,0.0007657854,0.000642881,0.0002877627,0.0007755579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002629067,"about_ca_system_score_gemma":0.0002584806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001541969,"about_ca_topic_score_gemma":0.003436297,"domain_scores_codex":[0.9988111,0.0006799678,0.00009015858,0.0001281166,0.0002338159,0.00005683346],"domain_scores_gemma":[0.9955225,0.002675323,0.000356732,0.0001901201,0.0009174506,0.0003377986],"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":[0.02478363,0.008596278,0.2011287,0.001620275,0.000506859,0.0002975567,0.006554513,0.006144879,0.08435925,0.001559829,0.01385198,0.6505963],"study_design_scores_gemma":[0.001188941,0.01465149,0.8080318,0.000318606,0.001031426,0.0003437208,0.005864948,0.1141783,0.0394433,0.003516359,0.01121049,0.0002206123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9847479,0.000259809,0.005378392,0.0002013093,0.00007929123,0.0004058671,0.0005467003,0.0001873284,0.008193415],"genre_scores_gemma":[0.9905372,0.00008812556,0.006781951,0.0001616928,0.00002851914,0.0002223585,0.0003912061,0.00002109321,0.001767825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004390043,"threshold_uncertainty_score":0.01468611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2888817990805223,"score_gpt":0.5453131383301174,"score_spread":0.2564313392495952,"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."}}