{"id":"W2810320099","doi":"10.1111/capa.12263","title":"Digital third parties: Understanding the technological challenge to Canada's third party advertising regime","year":2018,"lang":"en","type":"article","venue":"Canadian Public Administration","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Advertising; Third party; The Internet; Obstacle; Business; Social media; Political science; Internet privacy; Law; Computer science","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":[0.0003244353,0.0001612423,0.0001156911,0.0001512993,0.0008958166,0.001007601,0.0007305875,0.0001343552,0.00002093356],"category_scores_gemma":[0.0003408687,0.000130142,0.000036024,0.0006832171,0.0001548633,0.0005894934,0.00006937329,0.0002071932,0.00005462023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00104395,"about_ca_system_score_gemma":0.003403107,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04485593,"about_ca_topic_score_gemma":0.9824824,"domain_scores_codex":[0.9983389,0.00004788267,0.0002360632,0.0004162505,0.0003439293,0.0006169647],"domain_scores_gemma":[0.9985776,0.00005636518,0.00007552916,0.000572258,0.000119626,0.0005986434],"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":[0.00001211311,0.00002628741,0.0002802373,0.000007701166,0.00003381992,0.0001158891,0.0005224629,0.000002200851,0.00005706468,0.8778912,0.03352562,0.08752533],"study_design_scores_gemma":[0.0001677829,0.0005709581,0.0004131602,0.00003436572,0.000006345671,0.0001313536,0.001839487,0.003447981,0.0008999171,0.009980065,0.9820316,0.0004769126],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02823411,0.0000742016,0.4095525,0.4573386,0.001423556,0.0007959702,0.00003961156,0.0006292056,0.1019122],"genre_scores_gemma":[0.997066,0.000002147367,0.0003450578,0.001530849,0.0001822425,0.00002541353,0.000009527298,0.000008857006,0.0008299539],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9688318,"threshold_uncertainty_score":0.9716322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03203629545183775,"score_gpt":0.2313499278907134,"score_spread":0.1993136324388756,"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."}}