{"id":"W1994071237","doi":"10.1145/2857659.2857660","title":"27 <sup>th</sup> ACM International Conference on Hypertext and Social Media","year":2016,"lang":"en","type":"article","venue":"ACM SIGWEB Newsletter","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Hypertext; Computer science; Personalization; Social media; World Wide Web; Adaptation (eye); Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003839273,0.00157725,0.002369324,0.002517364,0.001503295,0.01008284,0.001797417,0.002235399,0.3261178],"category_scores_gemma":[0.009118258,0.0006127249,0.000941133,0.003038069,0.001395644,0.005519902,0.002856072,0.004334446,0.2362034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001072051,"about_ca_system_score_gemma":0.001770093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003285093,"about_ca_topic_score_gemma":0.007531263,"domain_scores_codex":[0.9978611,0.0005062685,0.0002335503,0.0002799902,0.0008870915,0.0002320749],"domain_scores_gemma":[0.9860646,0.004580839,0.0006278937,0.00114052,0.004867854,0.002718223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001121181,0.00004255502,0.0005100248,0.0002883617,0.00002364761,0.00009160661,0.000066541,0.00008090356,0.0008597876,0.001496295,0.9172823,0.07914585],"study_design_scores_gemma":[0.00002227589,0.00008312019,0.001704312,0.0002146705,0.00003107273,0.0001932542,0.0001976441,0.0007095971,0.0008102439,0.001043997,0.9949648,0.00002501774],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.006647814,0.04129563,0.07940844,0.04941519,0.3007166,0.001705958,0.02583522,0.01089239,0.4840828],"genre_scores_gemma":[0.01242427,0.01932172,0.01120267,0.006732127,0.04049915,0.0007939566,0.02457226,0.003441117,0.8810127],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3261178,"threshold_uncertainty_score":0.9612111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05820448069823664,"score_gpt":0.2715417705104575,"score_spread":0.2133372898122209,"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."}}