{"id":"W2952738255","doi":"","title":"Land Utilization in Carleton and Victoria Counties, New Brunswick","year":2016,"lang":"en","type":"article","venue":"Scientific Agriculture","topic":"Agriculture and Rural Development Research","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Geography; Forestry; Agricultural economics; Economics","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":[0.0005133805,0.0002458029,0.0004440075,0.002359959,0.002346403,0.001907442,0.001345951,0.000436924,0.002586165],"category_scores_gemma":[0.001671727,0.0004427485,0.0003893661,0.005689205,0.0007732976,0.00058272,0.001738388,0.0004197409,0.0003378516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02713042,"about_ca_system_score_gemma":0.02563982,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9812456,"about_ca_topic_score_gemma":0.9977787,"domain_scores_codex":[0.9991223,0.0001497068,0.00006000919,0.0001128468,0.0001769237,0.0003782241],"domain_scores_gemma":[0.9987475,0.0001891461,0.000196351,0.00004651335,0.0004833651,0.0003371142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003144625,0.00008120303,0.9571407,0.0002162797,0.0001338337,0.001134852,0.01001899,0.000799772,0.002652031,0.001247931,0.00388951,0.02237036],"study_design_scores_gemma":[0.000008101399,0.00001778984,0.9769932,0.00006308277,0.0000178476,0.0001172147,0.01858046,0.0003633506,0.0002002065,0.00006170462,0.003561274,0.00001568921],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919235,0.0005336855,0.00007211036,0.0002331097,0.000007408188,0.00005778459,0.002336417,0.000008359067,0.004827556],"genre_scores_gemma":[0.98825,0.0005278318,0.0004395301,0.0001092302,0.000002738215,0.00007552213,0.001490172,0.000009594532,0.009095445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02713042,"threshold_uncertainty_score":0.1968459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01985192837936883,"score_gpt":0.2238875902025737,"score_spread":0.2040356618232048,"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."}}