{"id":"W3215274613","doi":"10.3390/ijgi10120801","title":"Estimation of Agricultural Dykelands Cultivated in Nova Scotia Using Land Property Boundaries and Crop Inventory","year":2021,"lang":"en","type":"article","venue":"ISPRS International Journal of Geo-Information","topic":"Soil and Land Suitability Analysis","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Prince Edward Island; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Dalhousie University","keywords":"Nova scotia; Hectare; Agriculture; Crop; Forage; Geography; Agricultural land; Land use; Crop yield; Environmental science; Agricultural science; Agroforestry; Forestry; Agronomy; Biology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002904869,0.00006643143,0.0001309666,0.0001026016,0.00004577043,0.0001365444,0.000105175,0.00004377766,0.0002423471],"category_scores_gemma":[0.0002185811,0.0000417988,0.00005158229,0.0001789582,0.0001016278,0.002158132,0.00006180676,0.00009785218,0.000010056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001744523,"about_ca_system_score_gemma":0.00005073997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0018214,"about_ca_topic_score_gemma":0.0006402555,"domain_scores_codex":[0.9989362,0.00003823041,0.0004900463,0.00004865597,0.0004120838,0.00007479733],"domain_scores_gemma":[0.99941,0.00001909227,0.0003172198,0.00004489275,0.000173572,0.00003521293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001123703,0.00007895852,0.9115397,0.00002820178,0.00009035941,0.00000655718,0.004012089,0.05957523,0.001645311,0.00005663849,0.0002847851,0.02256979],"study_design_scores_gemma":[0.001087977,0.00004605405,0.9274034,0.000118268,0.00003619241,0.0001734259,0.0009849515,0.06505111,0.003659883,0.0002636756,0.001057492,0.0001175985],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972964,0.00002728374,0.001466827,0.0004063405,0.0002164206,0.00003592565,0.000006131497,0.000002709513,0.0005419482],"genre_scores_gemma":[0.9990152,0.00001283373,0.0008152943,0.00007122764,0.00002091823,2.782284e-7,0.00003934641,0.000001311217,0.00002360216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02245219,"threshold_uncertainty_score":0.2753424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009657700523526498,"score_gpt":0.240662698277797,"score_spread":0.2310049977542705,"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."}}