{"id":"W3031466865","doi":"","title":"ASSESSING REGIONAL AGROECOSYSTEM HEALTH COMBINING ECOLOGICAL-SOCIAL-ECONOMIC COMPONENTS USING CASE STUDIES OF NOVA SCOTIA AND FUJIAN PROVINCES","year":2019,"lang":"en","type":"article","venue":"","topic":"Agriculture and Biological Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Agroecosystem; Nova scotia; Geography; Ecology; Agriculture; Biology; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.00114029,0.000474033,0.0002811803,0.001478108,0.0007922193,0.00085653,0.0005126494,0.0003552714,0.0005239148],"category_scores_gemma":[0.002625897,0.0002274815,0.0005179736,0.002076968,0.0008936104,0.0003220823,0.0006317322,0.0002277219,0.00002822304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009080492,"about_ca_system_score_gemma":0.003471459,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8142319,"about_ca_topic_score_gemma":0.8818678,"domain_scores_codex":[0.9993953,0.000265101,0.00002565528,0.00006427999,0.0000661431,0.0001836474],"domain_scores_gemma":[0.9986355,0.0005478903,0.0002518167,0.00009297463,0.0003212089,0.0001506599],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003927572,0.0001478212,0.9597497,0.0000755205,0.0004231848,0.002232761,0.001132314,0.02654226,0.001760083,0.0008294252,0.0002315328,0.006482488],"study_design_scores_gemma":[0.00002537483,0.0001044634,0.978431,0.00002394549,0.0001594272,0.0001336738,0.004585766,0.01559528,0.0004199555,0.0001227625,0.0003851239,0.00001321326],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993232,0.00004767674,0.00008111603,0.00001688041,6.701789e-7,0.00001660783,0.0001097982,9.108567e-7,0.0004029569],"genre_scores_gemma":[0.99955,0.0000381047,0.0002048142,0.000003880913,4.263395e-7,0.000007109597,0.00008853873,4.308553e-7,0.0001065517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1857681,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.131947298089934,"score_gpt":0.3239953891366252,"score_spread":0.1920480910466912,"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."}}