{"id":"W2984009833","doi":"10.1016/j.gloenvcha.2019.102004","title":"Forest conversion by the indigenous Kalasha of Pakistan: A household level analysis of socioeconomic drivers","year":2019,"lang":"en","type":"article","venue":"Global Environmental Change","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Higher Education Commision, Pakistan","keywords":"Indigenous; Deforestation (computer science); Socioeconomic status; Clearing; Socioeconomics; Household income; Livestock; Geography; Business; Agriculture; Logging; Agroforestry; Forestry; Economics; Ecology; Population; Environmental health; Finance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001317163,0.0001396719,0.0002206718,0.00003937379,0.0001084599,0.000008596801,0.0003606192,0.00006665883,0.002219194],"category_scores_gemma":[7.879012e-7,0.000116437,0.0001821414,0.0001958606,0.0003668085,0.0001036271,0.0004467153,0.00004974596,0.0002690314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005362782,"about_ca_system_score_gemma":0.000003189857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003664256,"about_ca_topic_score_gemma":0.0003762523,"domain_scores_codex":[0.9989673,0.00003586675,0.0002042507,0.0002693241,0.000314375,0.0002088828],"domain_scores_gemma":[0.9994053,0.00001988238,0.0002142431,0.0003033005,0.000001242116,0.00005598973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002159021,0.0001069592,0.9957341,0.00001001913,0.0002164484,8.260191e-7,0.001226913,0.0007432314,0.0006645723,0.000004292242,0.0005630163,0.0007080223],"study_design_scores_gemma":[0.0003610915,0.00008013879,0.9887231,0.000002797773,0.0003087176,4.841607e-7,0.002530327,0.0004531496,0.0001843724,0.000007995664,0.007223287,0.0001245491],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967059,0.00008734531,0.00001489917,0.0001129694,0.00006671786,0.0004314651,0.001240925,0.000009294624,0.001330449],"genre_scores_gemma":[0.9989704,0.0001038796,0.00002206686,0.0003419437,0.000007674599,0.000005488312,0.0001295364,0.000005124522,0.0004138544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00701102,"threshold_uncertainty_score":0.9986929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01948818374091722,"score_gpt":0.1989651845718871,"score_spread":0.1794770008309699,"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."}}