{"id":"W4255331738","doi":"10.1016/s0969-4765(20)30126-0","title":"Canadian firm covertly captured 5m shoppers' images","year":2020,"lang":"en","type":"article","venue":"Biometric Technology Today","topic":"Legal and Policy Issues","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Real estate; Government (linguistics); Business; Biometrics; Estate; Internet privacy; Advertising; Face (sociological concept); Computer security; Finance; Computer science; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009791328,0.0004251285,0.0003487715,0.001998729,0.005712262,0.002370151,0.0007845807,0.0008504283,0.05361065],"category_scores_gemma":[0.002907356,0.000363915,0.0003050853,0.00247519,0.0009960576,0.0008577986,0.001200742,0.0007539554,0.009378262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01051142,"about_ca_system_score_gemma":0.01716292,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8743348,"about_ca_topic_score_gemma":0.9687228,"domain_scores_codex":[0.9982585,0.0000590496,0.00002622675,0.0001856506,0.001220968,0.0002495926],"domain_scores_gemma":[0.9964111,0.0002376795,0.0001163023,0.0002991188,0.002688467,0.0002473319],"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":[0.0004674984,0.0001914737,0.03302121,0.0003084877,0.00003605226,0.0008855351,0.004466081,0.0002482042,0.01607002,0.01460014,0.5313141,0.3983913],"study_design_scores_gemma":[0.00002465145,0.00008548861,0.08335871,0.0001745212,0.00003002438,0.0005648456,0.004838493,0.001836701,0.01022522,0.0006576338,0.8981134,0.00009020945],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.226254,0.001510636,0.009697516,0.01076699,0.0009427211,0.0008568141,0.01879633,0.002163009,0.729012],"genre_scores_gemma":[0.4664908,0.001069624,0.01927151,0.003467873,0.0001076383,0.0002026586,0.007382868,0.000293282,0.5017137],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1256652,"threshold_uncertainty_score":0.2528105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02491914051167269,"score_gpt":0.296966933127986,"score_spread":0.2720477926163133,"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."}}