{"id":"W1986795147","doi":"10.1016/j.ecolind.2013.11.003","title":"The calculation of productivity factor for ecological footprints in China: A methodological note","year":2013,"lang":"en","type":"article","venue":"Ecological Indicators","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"University of Guelph","keywords":"Arable land; Productivity; Primary production; Environmental science; Ecological footprint; Land use; Ecology; Ecosystem; Geography; Environmental resource management; Sustainable development; Agriculture; Economics; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006591117,0.0007018312,0.0007143466,0.003505753,0.00111445,0.002147418,0.00180286,0.0005448073,0.001332471],"category_scores_gemma":[0.01441408,0.0003467037,0.001110114,0.005896648,0.00107445,0.003210852,0.00147112,0.0009814131,0.0002003423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002789268,"about_ca_system_score_gemma":0.004914125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07802676,"about_ca_topic_score_gemma":0.06534107,"domain_scores_codex":[0.997321,0.001132915,0.0003604402,0.0005416085,0.0004806999,0.0001633862],"domain_scores_gemma":[0.9945533,0.001968591,0.0005521324,0.001278224,0.001523779,0.0001240218],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001745226,0.0001317423,0.2777997,0.0008548552,0.0004074931,0.0005555722,0.001745565,0.07103702,0.006393225,0.1825165,0.003727237,0.4546565],"study_design_scores_gemma":[0.00007265292,0.0002205889,0.387312,0.0003723497,0.0003208986,0.0005525475,0.002861448,0.376116,0.01221661,0.1880055,0.03174892,0.0002005168],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2765703,0.002149061,0.7087444,0.001172168,0.0001819818,0.0004049765,0.002014,0.0002766264,0.008486487],"genre_scores_gemma":[0.7725445,0.0008226144,0.2227411,0.00007364594,0.000075273,0.0003677798,0.0009846165,0.00008602777,0.002304427],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07802676,"threshold_uncertainty_score":0.1551452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03154992661817452,"score_gpt":0.3177150436309469,"score_spread":0.2861651170127724,"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."}}