{"id":"W4385417916","doi":"10.1163/9789004322714_cclc_2020-0051-0273","title":"THE LOGGING LOOPHOLE: HOW THE LOGGING INDUSTRY’S UNREGULATED CARBON EMISSIONS UNDERMINE CANADA’S CLIMATE GOALS","year":2023,"lang":"en","type":"dataset","venue":"Climate Change and Law Collection","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Logging; Natural resource economics; Climate change; Greenhouse gas; Business; Environmental science; Environmental resource management; Forestry; Geography; Ecology; Economics","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0007137728,0.0004245495,0.0003247377,0.00004459504,0.003172246,0.0002592305,0.0003543622,0.0004844077,0.0001227266],"category_scores_gemma":[0.00007462851,0.0002737748,0.0000674753,0.0004738827,0.0005796408,0.0001549296,0.0007743744,0.0009003119,0.00002361715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00152164,"about_ca_system_score_gemma":0.00007097108,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5209629,"about_ca_topic_score_gemma":0.7686097,"domain_scores_codex":[0.9974945,0.0002397098,0.0003113375,0.0005576986,0.0004636289,0.0009331414],"domain_scores_gemma":[0.9986356,0.0002491699,0.0002586711,0.0006334881,0.00001018492,0.0002128332],"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":[0.00003405658,0.00003952072,0.001792441,0.0001358226,0.00003168873,0.00005176623,0.0001726195,0.00004471945,0.0000711051,0.00001117236,0.9971076,0.0005074885],"study_design_scores_gemma":[0.0003374798,0.00009359439,0.01486672,0.0001186541,0.0001487024,0.00004399123,0.002675495,0.0007959997,0.00007291151,0.0001121527,0.9802507,0.0004836594],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1893991,0.001457741,8.965948e-7,0.02537225,0.003342338,0.004302023,0.7723288,0.0002972054,0.003499661],"genre_scores_gemma":[0.3097002,0.03414984,0.000007725617,0.005078831,0.001617218,0.001309555,0.6341496,0.0003179362,0.0136691],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2476468,"threshold_uncertainty_score":0.9999714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03389837054735892,"score_gpt":0.2563500989739955,"score_spread":0.2224517284266366,"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."}}