{"id":"W2897980426","doi":"10.1145/3269206.3269313","title":"Predicting Personal Life Events from Streaming Social Content","year":2018,"lang":"en","type":"article","venue":"","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Event (particle physics); Computer science; Personal life; Relevance (law); Social media; Task (project management); Predictive power; World Wide Web; Engineering","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":[0.0009635267,0.0005786949,0.000504809,0.002114047,0.0003168487,0.0007719841,0.0006567145,0.0009433514,0.001318429],"category_scores_gemma":[0.005911257,0.0003001458,0.000480865,0.001378029,0.0001748433,0.001833371,0.0004357394,0.0007588313,0.0008749982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004167538,"about_ca_system_score_gemma":0.0002271393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006175178,"about_ca_topic_score_gemma":0.010595,"domain_scores_codex":[0.9996499,0.0001007844,0.00002860877,0.00009690545,0.00008940332,0.00003440493],"domain_scores_gemma":[0.9964379,0.00234177,0.0004085648,0.0002971944,0.0003639191,0.0001505977],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001296584,0.000839319,0.4615877,0.0005781999,0.0004745106,0.001201784,0.001249967,0.1256306,0.01449362,0.006045604,0.01411677,0.3724854],"study_design_scores_gemma":[0.00001628006,0.0002124964,0.07300899,0.00005317488,0.00009023339,0.0004380047,0.0003520039,0.913028,0.003312087,0.005285498,0.00416513,0.00003816421],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.855568,0.002053661,0.1261799,0.001138029,0.0001873986,0.0002889814,0.007913033,0.001136935,0.005534125],"genre_scores_gemma":[0.9623851,0.0006119679,0.03110969,0.00006701968,0.0001109031,0.00006100256,0.004408542,0.00002334923,0.001222368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006175178,"threshold_uncertainty_score":0.0122785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06972244855743445,"score_gpt":0.2738176465067327,"score_spread":0.2040951979492983,"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."}}