{"id":"W2296431343","doi":"","title":"Implementing technology in the justice sector: A Canadian perspective.","year":2013,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Artificial Intelligence in Law","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Ottawa","funders":"Université de Montréal","keywords":"Economic Justice; Process (computing); Perspective (graphical); Exploratory research; Technological change; Public relations; Emerging technologies; Grounded theory; Politics; Business; Political science; Sociology; Law; Qualitative research; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001143518,0.0001201444,0.0001296311,0.0001630793,0.001432844,0.0002777692,0.0008150008,0.0001610059,0.005297561],"category_scores_gemma":[0.001008335,0.0001034105,0.00004759638,0.0008653693,0.0005497877,0.0004075383,0.00006600864,0.0004264572,0.002063767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000620116,"about_ca_system_score_gemma":0.0004421912,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9549189,"about_ca_topic_score_gemma":0.9911812,"domain_scores_codex":[0.997919,0.0002376445,0.0002470496,0.0002907542,0.0002980849,0.001007431],"domain_scores_gemma":[0.998958,0.000246448,0.00006576783,0.0003215465,0.0001974095,0.0002108325],"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":[8.234857e-7,0.00001579614,0.005400911,0.000002524653,0.000005517131,0.000008694727,0.0092649,0.000004974392,0.0001512853,0.9821781,0.00235377,0.000612685],"study_design_scores_gemma":[0.00007393467,0.00003426366,0.001561689,0.00002139587,0.00002697025,0.000003867312,0.3264089,0.00005660822,0.0003881318,0.2135527,0.4575934,0.0002780881],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4101857,0.0002496311,0.00004133642,0.0444998,0.0004884614,0.0009047436,0.000007711774,0.0001153002,0.5435073],"genre_scores_gemma":[0.9962693,0.0000162348,0.000253049,0.002224195,0.0004102562,0.0001138627,0.000001136923,0.00001319583,0.0006987932],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7686254,"threshold_uncertainty_score":0.9998671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03310240727354965,"score_gpt":0.3272032048057536,"score_spread":0.294100797532204,"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."}}