{"id":"W2301488944","doi":"10.1017/s1472669616000050","title":"The Intersection of Freedom of Information, Privacy Legislation and Library Services in Canadian Jurisdictions","year":2016,"lang":"en","type":"article","venue":"Legal Information Management","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Legislation; Notice; Freedom of information; Confidentiality; Privacy law; Privacy policy; Intersection (aeronautics); Relation (database); Law; Internet privacy; Intellectual freedom; Business; Political science; Information privacy; Computer science; Censorship; Engineering; Database","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005388333,0.00005742154,0.00006468636,0.0003286601,0.0002797876,0.0001647257,0.0002421597,0.00005066064,0.00002971282],"category_scores_gemma":[0.00006899844,0.00004189822,0.00002035412,0.0003574788,0.0001096526,0.01114316,0.0001188408,0.00005014776,0.00001522457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001229133,"about_ca_system_score_gemma":0.0001016158,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1990756,"about_ca_topic_score_gemma":0.1835681,"domain_scores_codex":[0.9991152,0.0000580078,0.0004116244,0.00004650881,0.0002114739,0.0001571723],"domain_scores_gemma":[0.9994209,0.00003732641,0.0002345585,0.0001732102,0.00007310899,0.00006085448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006539822,0.00001835274,0.01490667,0.0001790023,0.00003651279,1.757077e-7,0.03382434,0.0001019872,0.000007149486,0.7647718,0.003527032,0.1825616],"study_design_scores_gemma":[0.0003845442,0.00002775288,0.08071153,0.00007710069,0.000008122101,3.343773e-7,0.005741205,0.0008448607,0.00004356819,0.005385182,0.9067052,0.00007056782],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2491937,0.0001739405,0.04309815,0.03730121,0.002386584,0.00380012,0.000308289,0.0002656911,0.6634724],"genre_scores_gemma":[0.9988769,0.0003638756,0.0004561027,0.00009415202,0.00003113537,0.00002766898,0.00003940877,0.00000189795,0.0001088988],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9031782,"threshold_uncertainty_score":0.8313296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00710897612565106,"score_gpt":0.232370729037758,"score_spread":0.225261752912107,"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."}}