{"id":"W4413575767","doi":"10.51644/bap75","title":"Code Before Clause: Building Canada’s Digital Defences Before Negotiating Trade","year":2025,"lang":"en","type":"article","venue":"Balsillie Papers","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Negotiation; Code (set theory); Computer science; Business; Programming language; International trade; Political science; Computer security; Law","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":[0.01282513,0.00078877,0.0006089328,0.002392688,0.0282146,0.02479693,0.003676204,0.01408641,0.02580597],"category_scores_gemma":[0.04175455,0.000991325,0.001082145,0.002780146,0.02085824,0.009271638,0.009779898,0.01490244,0.003862562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1066438,"about_ca_system_score_gemma":0.3398123,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.955571,"about_ca_topic_score_gemma":0.9615002,"domain_scores_codex":[0.9785196,0.002857374,0.0005953552,0.002154918,0.009917304,0.005955395],"domain_scores_gemma":[0.9702724,0.008295138,0.0009152803,0.002548869,0.01172416,0.006244236],"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":[0.00001862355,0.00002104268,0.0009226346,0.00004722373,0.000008401067,0.0003406108,0.00450563,0.000480272,0.0002783755,0.8585581,0.120076,0.01474305],"study_design_scores_gemma":[0.00002234899,0.00001303931,0.001036957,0.0002462269,0.00001256613,0.0000890392,0.003747722,0.0005537538,0.0003754626,0.03962214,0.9542052,0.00007546374],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.01253544,0.002147643,0.01780299,0.1774514,0.002203983,0.0003236071,0.0005362609,0.0004120271,0.7865866],"genre_scores_gemma":[0.3884372,0.002559852,0.01931116,0.1599753,0.000614967,0.0004879728,0.0009622772,0.0005628168,0.4270884],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.1066438,"threshold_uncertainty_score":0.7737585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007805416221629373,"score_gpt":0.2610254948724437,"score_spread":0.2532200786508143,"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."}}