{"id":"W1863738141","doi":"10.32920/ryerson.14660694","title":"Identity matching in social media platforms","year":2021,"lang":"en","type":"article","venue":"","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Matching (statistics); Social media; Identity (music); Set (abstract data type); Task (project management); Information retrieval; World Wide Web; Similarity (geometry); Process (computing); Social Semantic Web; Semantic Web; Artificial intelligence; Mathematics; Engineering","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":[0.009021631,0.0004202901,0.0006824528,0.007971009,0.002708813,0.004740768,0.001689572,0.001758804,0.002641422],"category_scores_gemma":[0.0283046,0.0003638618,0.00100913,0.006345511,0.001448484,0.008168316,0.004907624,0.0007954846,0.001022796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002103992,"about_ca_system_score_gemma":0.002128678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005012995,"about_ca_topic_score_gemma":0.003376781,"domain_scores_codex":[0.9867718,0.005019026,0.0009131887,0.001815951,0.00460972,0.0008703065],"domain_scores_gemma":[0.9882686,0.005192554,0.002718249,0.001632725,0.001792419,0.0003955097],"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":[0.0005950257,0.0006874631,0.09961914,0.0006213164,0.0003287354,0.002044696,0.003530419,0.04839177,0.007021518,0.3231362,0.00964916,0.5043746],"study_design_scores_gemma":[0.00004849619,0.0003132558,0.03277044,0.0003951598,0.0001568474,0.001600938,0.008295743,0.5472046,0.01988358,0.3409506,0.0482343,0.0001460358],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3418806,0.001203648,0.6140053,0.002566988,0.0002013205,0.001283868,0.001960234,0.0007523124,0.03614567],"genre_scores_gemma":[0.8585778,0.0004838708,0.1351598,0.0001626321,0.00007226247,0.0002843082,0.001137944,0.00004116586,0.004080193],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009021631,"threshold_uncertainty_score":0.04771149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2828132511239933,"score_gpt":0.4597413444349298,"score_spread":0.1769280933109365,"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."}}