{"id":"W4322743588","doi":"10.1016/j.diggeo.2023.100053","title":"Reconceptualizing carbon datafication through indigeneity","year":2023,"lang":"en","type":"article","venue":"Digital Geography and Society","topic":"Water Governance and Infrastructure","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian International Development Agency","keywords":"Indigenous; Geographer; Context (archaeology); Agency (philosophy); Sociology; Geography; Economic geography; Social science; Archaeology; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001625369,0.00007785057,0.00008666486,0.00001589264,0.0004427402,0.0002094035,0.0001232194,0.0001026703,0.000009674696],"category_scores_gemma":[0.00002622299,0.00007348179,0.0001093037,0.0005254079,0.0003399293,0.000796851,0.00004755843,0.00009033649,0.00000683163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001308483,"about_ca_system_score_gemma":0.00003133069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007126064,"about_ca_topic_score_gemma":0.00004035997,"domain_scores_codex":[0.9992162,0.00001904897,0.0001032412,0.0002018461,0.0002020401,0.0002576369],"domain_scores_gemma":[0.9997152,0.00003343239,0.00005387321,0.0001125278,0.00003119592,0.00005378455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000004235081,0.00002659429,0.7427458,0.00002656957,0.00008996908,0.000001953608,0.1987292,0.000004525494,0.00006561897,0.01825478,0.01160786,0.028443],"study_design_scores_gemma":[0.0002537698,0.00002572336,0.499282,0.00002431199,0.0000142915,5.528731e-7,0.0610958,0.00002868836,0.0002104501,0.01959033,0.41915,0.0003240953],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9498098,0.0001460301,0.00001744238,0.000261091,0.0001651513,0.00009788604,0.00007607041,0.0001644448,0.04926207],"genre_scores_gemma":[0.9975508,0.001597578,0.00007028052,0.000212128,0.000172565,0.000006299214,0.00009906746,0.00000595156,0.00028537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4075421,"threshold_uncertainty_score":0.3405245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02285013617369443,"score_gpt":0.2778284960600912,"score_spread":0.2549783598863968,"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."}}