{"id":"W4205569544","doi":"10.1007/s10980-021-01397-2","title":"Explaining land use and forest change: more theory or better methodology?","year":2022,"lang":"en","type":"article","venue":"Landscape Ecology","topic":"Conservation, Biodiversity, and Resource Management","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Mount Allison University","funders":"Social Sciences and Humanities Research Council of Canada; Mount Allison University","keywords":"Reforestation; Variety (cybernetics); Causal model; Landscape ecology; Causal decision theory; Theory of change; Land use, land-use change and forestry; Transdisciplinarity; Sociology; Land use; Deforestation (computer science); Phenomenon; Environmental change; Epistemology; Causal theory of reference; Ecology; Climate change; Social science; Economics; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03847115,0.002169102,0.004359291,0.003885695,0.00156993,0.008215749,0.007351357,0.006135495,0.01377651],"category_scores_gemma":[0.08636887,0.001220786,0.002628101,0.00506264,0.01253353,0.01987563,0.004059363,0.009740983,0.001418971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003575464,"about_ca_system_score_gemma":0.007548777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01822206,"about_ca_topic_score_gemma":0.01581444,"domain_scores_codex":[0.985288,0.01108203,0.0005944078,0.001377939,0.001165972,0.0004915962],"domain_scores_gemma":[0.912457,0.07202566,0.004147881,0.006798584,0.003204293,0.001366611],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001448158,0.001252603,0.05380654,0.003555216,0.002033724,0.0002421117,0.002197109,0.03504173,0.0005074328,0.684418,0.01663357,0.2001672],"study_design_scores_gemma":[0.00008522515,0.00008628775,0.00601971,0.0007623191,0.0002201505,0.00008630552,0.001777841,0.0399256,0.0001823655,0.939832,0.01093302,0.00008916345],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07557236,0.05334398,0.5805447,0.2641292,0.004187897,0.0004341256,0.001304642,0.0006773173,0.01980581],"genre_scores_gemma":[0.6980147,0.0342951,0.2273588,0.02574343,0.007993463,0.001103917,0.001130834,0.0004153288,0.003944418],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9615288,"threshold_uncertainty_score":0.2034573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07602444572035266,"score_gpt":0.2538027401906257,"score_spread":0.177778294470273,"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."}}