{"id":"W2570211654","doi":"","title":"Carbon Credit Program in Alberta, Canada : Carbon Offset Credit by Portable Chipping","year":2013,"lang":"en","type":"article","venue":"Parupu kami kōgyō zasshi/Parupu kami kougyou zasshi","topic":"Sustainable Industrial Ecology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Carbon offset; Carbon fibers; Offset (computer science); Carbon credit; Business; Greenhouse gas; Computer science; Geology; Oceanography","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":[0.000439507,0.0002258059,0.0001690092,0.0007810311,0.002185794,0.001551317,0.001128034,0.001276166,0.01215668],"category_scores_gemma":[0.0009680479,0.0002098853,0.0002241724,0.001283602,0.0005311189,0.0004514976,0.0008765984,0.001063272,0.0004592796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02138211,"about_ca_system_score_gemma":0.09029151,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9745161,"about_ca_topic_score_gemma":0.9912698,"domain_scores_codex":[0.9993412,0.0000281833,0.00001060008,0.00003850327,0.0002181606,0.0003634206],"domain_scores_gemma":[0.9990558,0.00005099081,0.00003426471,0.00002487614,0.0004012131,0.0004328447],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001243793,0.001155346,0.2391583,0.0003815516,0.0001017279,0.003029095,0.001979487,0.008636639,0.007005025,0.0479655,0.3584431,0.3309005],"study_design_scores_gemma":[0.0003386616,0.0002392893,0.5654749,0.000136611,0.0000866326,0.0003323546,0.005051039,0.00607078,0.002746753,0.002113116,0.4173062,0.0001037796],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.742977,0.002130177,0.001102527,0.02113875,0.0005109571,0.000523279,0.01187764,0.0004526544,0.2192871],"genre_scores_gemma":[0.8160522,0.0008122235,0.001152164,0.00189941,0.00005455872,0.00008679293,0.003075957,0.00004610461,0.1768206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02548391,"threshold_uncertainty_score":0.1551388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006227238678930901,"score_gpt":0.1952411321695134,"score_spread":0.1890138934905825,"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."}}