{"id":"W4413558175","doi":"10.64628/aam.mfxxgeaf6","title":"Companies are increasingly turning to social media to screen potential employees","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Social media; Business; Advertising; Computer science; World Wide Web","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000805509,0.0003302825,0.0005575279,0.0002298838,0.001225617,0.0007877609,0.001604108,0.0004646868,0.0003470447],"category_scores_gemma":[0.003754372,0.0003536844,0.0001925155,0.0004331841,0.0001645581,0.0002352036,0.004429692,0.0007731309,0.0003617121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002568931,"about_ca_system_score_gemma":0.0003715975,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03397879,"about_ca_topic_score_gemma":0.04191047,"domain_scores_codex":[0.9966943,0.0005059556,0.0003978931,0.0008166454,0.001024761,0.0005604727],"domain_scores_gemma":[0.9984444,0.0001394125,0.000210949,0.0003780329,0.0002638052,0.0005634096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001089481,0.00051227,0.00569758,0.0004159865,0.0005133494,0.0001454557,0.4868663,0.0003844734,0.00164918,0.03167424,0.4343978,0.03665389],"study_design_scores_gemma":[0.001763734,0.0004759968,0.2455152,0.001075342,0.0005697832,0.000007749818,0.15829,0.0003650546,0.001187583,0.2080815,0.3768039,0.005864096],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8064094,0.0002096057,0.03845636,0.1166098,0.006011564,0.003142069,0.001619649,0.00235913,0.0251825],"genre_scores_gemma":[0.985472,0.00002931775,0.006513818,0.001315948,0.006279788,0.00006385839,0.000200979,0.00003773781,0.00008660885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3285762,"threshold_uncertainty_score":0.9998915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06337201497188318,"score_gpt":0.3225998823978937,"score_spread":0.2592278674260105,"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."}}