{"id":"W4212983095","doi":"10.1163/9789004322714_cclc_2018-0051-016","title":"Statement on Canada’s plan to ensure that polluters pay for their carbon emissions in every province","year":2019,"lang":"en","type":"dataset","venue":"Climate Change and Law Collection","topic":"Environmental Policies and Emissions","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Statement (logic); Plan (archaeology); Environmental impact statement; Carbon fibers; Business; Environmental protection; Geography; Political science; Law; Archaeology; Computer science; Environmental impact assessment","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":[0.0001280718,0.0002791363,0.0002555884,0.00005936439,0.0003252543,0.00003075974,0.0001378164,0.0001580303,0.0001641859],"category_scores_gemma":[0.000006824738,0.0002028322,0.00003876435,0.0001126916,0.00003753911,0.00006146791,0.0002059554,0.0001894607,0.00001130935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001152931,"about_ca_system_score_gemma":0.00004744123,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5178112,"about_ca_topic_score_gemma":0.8519104,"domain_scores_codex":[0.9986224,0.00003833006,0.0002035117,0.000456175,0.0002250335,0.0004545599],"domain_scores_gemma":[0.9993635,0.00005966741,0.0001035992,0.0002799881,0.000001870741,0.0001913896],"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":[0.00007581737,0.00006117705,0.0005479248,0.0001022472,0.000006978189,0.00000451808,0.0002086285,0.00008409889,0.0001315946,0.000002078206,0.9985484,0.0002265372],"study_design_scores_gemma":[0.0003045623,0.0002935303,0.004729519,0.0002139732,0.00001841859,0.0000028026,0.0003687266,0.0000835415,0.0002062992,0.000008542734,0.9934747,0.0002953815],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02148326,0.00005213575,5.128206e-7,0.002364526,0.0006697943,0.002177611,0.9721546,0.00001263452,0.001084944],"genre_scores_gemma":[0.06124696,0.004708292,0.00004049514,0.01102352,0.0004540803,0.001575338,0.9139451,0.0001154293,0.00689078],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3340992,"threshold_uncertainty_score":0.8271258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04620849916745557,"score_gpt":0.248396998425714,"score_spread":0.2021884992582584,"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."}}