{"id":"W2944499528","doi":"10.3390/su11092716","title":"Telecoupled Sustainable Livelihoods in an Era of Rural–Urban Dynamics: The Case of China","year":2019,"lang":"en","type":"article","venue":"Sustainability","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Livelihood; Diversification (marketing strategy); Context (archaeology); China; Urbanization; Agrarian society; Environmental planning; Sustainable development; Natural resource economics; Business; Economic growth; Geography; Agriculture; Economics; Political science","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":[],"consensus_categories":[],"category_scores_codex":[0.001070161,0.0001359051,0.0002765536,0.00003235027,0.00007682134,0.00001778698,0.0003678041,0.00007710515,0.0008118013],"category_scores_gemma":[0.00008511101,0.00008915399,0.00006943792,0.0004317934,0.00007489361,0.0004215754,0.0002590724,0.0001716143,0.00001193748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007270729,"about_ca_system_score_gemma":0.00008439149,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0561446,"about_ca_topic_score_gemma":0.02024489,"domain_scores_codex":[0.9986574,0.0001784569,0.0003844885,0.0002290925,0.0001487526,0.0004017996],"domain_scores_gemma":[0.9988992,0.00008009483,0.0001564859,0.0007152596,0.00008651113,0.00006245993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006680977,0.0002295595,0.9904129,0.0005736072,0.000006217278,0.00006170855,0.003729457,0.00236861,0.00003515649,0.0008759389,0.00001457159,0.001625444],"study_design_scores_gemma":[0.000618381,0.0003738226,0.8879751,0.00002265569,0.00001643624,0.00003074549,0.05980649,0.03924173,0.0002269482,0.01140462,0.00007862401,0.0002044638],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978415,0.00004351457,0.000008376187,0.0003165388,0.00003447227,0.0008681908,0.000007870347,0.00001371318,0.000865815],"genre_scores_gemma":[0.9997693,0.000004375883,0.00001992681,0.00001596292,0.00001057477,0.00002129607,0.000006626083,0.000009839936,0.000142087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1024378,"threshold_uncertainty_score":0.9976331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002330194957924872,"score_gpt":0.2142027048887162,"score_spread":0.2118725099307914,"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."}}