{"id":"W1798084261","doi":"10.1016/j.jrurstud.2015.09.007","title":"“Communities in the middle”: Interactions between drivers of change and place-based characteristics in rural forest-based communities","year":2015,"lang":"en","type":"article","venue":"Journal of Rural Studies","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Social Science Fund of China; National Socio-Environmental Synthesis Center; National Science Foundation","keywords":"Geography; Climate change; Wilderness; Environmental resource management; Adaptability; Economic geography; Resource (disambiguation); Diversity (politics); Demographic change; Population; Ecology; Sociology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002977687,0.0002763238,0.0004020352,0.003085864,0.002222162,0.003134704,0.0008343669,0.000748819,0.002319459],"category_scores_gemma":[0.008524419,0.0002044126,0.0006119807,0.003591426,0.003554635,0.005277367,0.004896304,0.001051294,0.00008046142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002475797,"about_ca_system_score_gemma":0.001727928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02697856,"about_ca_topic_score_gemma":0.04517734,"domain_scores_codex":[0.9980125,0.001121579,0.00006654869,0.0003676177,0.0001504775,0.0002812118],"domain_scores_gemma":[0.9961224,0.00183717,0.0008909358,0.0003058097,0.0002970354,0.0005465965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001578845,0.0002006588,0.8050887,0.00046966,0.0005930381,0.0004053314,0.06364571,0.002760686,0.0006745168,0.06534369,0.001192797,0.05946744],"study_design_scores_gemma":[0.00002211893,0.0001971702,0.7767606,0.0005050836,0.0002753928,0.0002594736,0.1067089,0.009191035,0.0003796154,0.09308525,0.01251968,0.00009572721],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9815655,0.001579145,0.007628489,0.003504161,0.00003742474,0.00006752456,0.0003601136,0.00002411484,0.00523349],"genre_scores_gemma":[0.9985974,0.0001915277,0.0009407589,0.00008429811,0.000005873096,0.0000223508,0.00006607352,0.000003263846,0.00008848828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02697856,"threshold_uncertainty_score":0.05364305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1933830339310555,"score_gpt":0.3124000506478697,"score_spread":0.1190170167168142,"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."}}