{"id":"W4416728359","doi":"10.1109/igarss55030.2025.11243595","title":"Mapping N <sub>2</sub> O Emission Hotspots in Canadian Prairie Croplands: A Focus on Rule-Based Scenarios as base modelling architectural framework for a Hierarchical Classification Model","year":2025,"lang":"","type":"article","venue":"","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Canadian Space Agency","keywords":"Baseline (sea); Greenhouse gas; Vulnerability (computing); Agriculture; Climate change; Scenario analysis; Key (lock); Risk management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004901264,0.0006393438,0.0002461723,0.001492019,0.0009657586,0.002363243,0.001619625,0.0004962817,0.001934742],"category_scores_gemma":[0.0009987188,0.0003133092,0.0009376589,0.001826638,0.0006470985,0.0007374689,0.0006931555,0.0004105531,0.0002407289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01257159,"about_ca_system_score_gemma":0.00891234,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9688957,"about_ca_topic_score_gemma":0.9753111,"domain_scores_codex":[0.9996964,0.00004563562,0.00001386062,0.00008110167,0.00008071264,0.00008239243],"domain_scores_gemma":[0.9996803,0.00008031728,0.00002812181,0.0000266567,0.0001483522,0.00003624917],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007199208,0.00004917188,0.0298998,0.00009170769,0.00008622184,0.0001771445,0.0004368296,0.9210994,0.002269954,0.0109163,0.003009328,0.03189215],"study_design_scores_gemma":[0.00001156898,0.00001203799,0.01603529,0.00003127684,0.00003479865,0.00002943594,0.0006128697,0.9739572,0.0006268903,0.003821597,0.004790383,0.00003666277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7543693,0.0006875248,0.1699688,0.002232411,0.00004820095,0.0007348839,0.01985442,0.00152667,0.05057787],"genre_scores_gemma":[0.9021194,0.0005471309,0.0841914,0.00007933396,0.00000617832,0.0001512925,0.006763124,0.00007602128,0.006066126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03110427,"threshold_uncertainty_score":0.0912137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03449264821777433,"score_gpt":0.2912066177515972,"score_spread":0.2567139695338229,"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."}}