{"id":"W4387271805","doi":"10.2139/ssrn.4562699","title":"Comments on 'Canadian Guardrails for Generative AI – Code of Practice'","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Generative grammar; Code (set theory); Code of practice; Computer science; Artificial intelligence; Programming language; Engineering; Engineering ethics; Set (abstract data type)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0183927,0.001750369,0.001771424,0.002359764,0.02515103,0.01373709,0.008028853,0.07812345,0.03592681],"category_scores_gemma":[0.1369911,0.001643026,0.002008401,0.003464459,0.01192892,0.008590394,0.007312605,0.06466708,0.01154295],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03510217,"about_ca_system_score_gemma":0.04826374,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6593866,"about_ca_topic_score_gemma":0.7346566,"domain_scores_codex":[0.9720672,0.004538805,0.001455794,0.003147583,0.01445887,0.004331691],"domain_scores_gemma":[0.9059134,0.04485593,0.003078071,0.003673345,0.03559486,0.006884487],"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":[0.00001720709,0.000003986054,0.00005888914,0.00002348821,0.000002692196,0.0000853502,0.0007541495,0.00006211367,0.00004673159,0.005728347,0.9921745,0.001042641],"study_design_scores_gemma":[0.00001649155,0.000009211622,0.0005683631,0.0001077704,0.00000689436,0.00005156671,0.001102887,0.0001316069,0.0001376187,0.001812456,0.9959862,0.00006899651],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0004326814,0.0008114959,0.0004367734,0.9672322,0.02026536,0.00002946806,0.0001730993,0.0001325265,0.01048638],"genre_scores_gemma":[0.008883989,0.0006594349,0.0008822708,0.8942912,0.01146901,0.000135296,0.0001275244,0.0003586806,0.08319262],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9648978,"threshold_uncertainty_score":0.6852387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01901172638986167,"score_gpt":0.3014928401602893,"score_spread":0.2824811137704276,"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."}}