{"id":"W3122490541","doi":"10.5751/es-12122-260103","title":"Linking the social, economic, and agroecological: a resilience framework for dairy farming","year":2021,"lang":"en","type":"article","venue":"Ecology and Society","topic":"Agriculture and Rural Development Research","field":"Agricultural and Biological Sciences","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agroecology; Resilience (materials science); Environmental resource management; Agriculture; Dairy farming; Psychological resilience; Business; Natural resource economics; Agroforestry; Environmental planning; Geography; Environmental science; Ecology; Economics; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0003422827,0.00008317448,0.0001357679,0.000001380092,0.001478359,0.00006872759,0.0001087408,0.0002347977,0.000155048],"category_scores_gemma":[0.00005898018,0.00002600735,0.00008059047,0.00006991456,0.0002035956,0.00005186628,0.0001660882,0.0002052884,0.000006104235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002026336,"about_ca_system_score_gemma":0.00001907618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008846855,"about_ca_topic_score_gemma":0.0002302826,"domain_scores_codex":[0.9992555,0.00006503404,0.0001144058,0.0002566558,0.00004809706,0.0002602447],"domain_scores_gemma":[0.9988036,0.001052756,0.00004284196,0.00002180504,0.00003619982,0.00004278523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007768544,0.0002375881,0.3413934,0.0001166464,0.000342736,0.0000286691,0.01306512,0.000006303816,0.03204456,0.2211927,0.1129871,0.2785074],"study_design_scores_gemma":[0.00008980229,0.00007152942,0.9316358,0.000006531442,0.00001003197,0.00001303673,0.004479004,0.00004140825,0.0001913496,0.02037888,0.04297053,0.0001120821],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9675779,0.0004959016,0.0000340847,0.0312609,0.000102841,0.0001731713,0.000008080332,0.00002271885,0.0003244352],"genre_scores_gemma":[0.993524,0.001267974,0.00130643,0.002530458,0.0003622668,0.0000499423,0.00002482031,5.916589e-7,0.0009335629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5902424,"threshold_uncertainty_score":0.9998216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02191297091123426,"score_gpt":0.2756625725116413,"score_spread":0.2537496016004071,"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."}}