{"id":"W2535417637","doi":"10.1145/2983323.2983827","title":"From Recommendation to Profile Inference (Rec2PI)","year":2016,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Recommender system; Inference; Context (archaeology); The Internet; Data science; Scope (computer science); Process (computing); Quality (philosophy); Data mining; World Wide Web; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.007694843,0.002535071,0.00312972,0.002756972,0.001091654,0.002394174,0.00535112,0.00260678,0.00211162],"category_scores_gemma":[0.03697914,0.001867061,0.001978846,0.004471404,0.0008097088,0.003823913,0.003122079,0.004457215,0.002369525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001249588,"about_ca_system_score_gemma":0.002665122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01923172,"about_ca_topic_score_gemma":0.02558923,"domain_scores_codex":[0.9936225,0.002882216,0.0003494127,0.001535877,0.001265471,0.0003445573],"domain_scores_gemma":[0.9735454,0.01684922,0.0009587768,0.005886069,0.002419743,0.0003407669],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004382051,0.0005552958,0.01299265,0.0007815512,0.001012068,0.0005415485,0.0005133291,0.1981445,0.002505473,0.02643135,0.02331534,0.7327687],"study_design_scores_gemma":[0.00004485173,0.0000783927,0.001133342,0.00005896588,0.00009478519,0.0003452313,0.00007143661,0.9617379,0.001909832,0.02974716,0.004727827,0.00005024382],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004592489,0.0006806621,0.9912837,0.000407128,0.000098418,0.0001928268,0.0005093999,0.001407366,0.000827947],"genre_scores_gemma":[0.1930724,0.001133775,0.7981332,0.0008439058,0.0003729383,0.0003886342,0.003048252,0.0002838334,0.002723102],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01923172,"threshold_uncertainty_score":0.04069471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03029894752626068,"score_gpt":0.2935031062388504,"score_spread":0.2632041587125897,"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."}}