{"id":"W2606093321","doi":"","title":"A methodology proposal for land cover change analysis using historical aerial photos","year":2011,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Rimouski","funders":"","keywords":"Orthophoto; Land cover; Computer science; Thematic map; Comparability; Remote sensing; Segmentation; Change detection; Aerial image; Aerial photography; Geography; Cartography; Land use; Artificial intelligence; Mathematics; Civil engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004458762,0.0002890452,0.0005953645,0.0001473907,0.0002749132,0.0001249391,0.0008950584,0.0003592684,0.001313766],"category_scores_gemma":[0.0002797726,0.0002601746,0.0003579266,0.0003873863,0.00005638677,0.0001522526,0.001293525,0.0002617761,0.00006875825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004599881,"about_ca_system_score_gemma":0.00008740765,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03222375,"about_ca_topic_score_gemma":0.0270285,"domain_scores_codex":[0.9947835,0.003303902,0.0004530663,0.0007958808,0.0002831006,0.0003806126],"domain_scores_gemma":[0.9972738,0.0006214495,0.0005157397,0.001205974,0.0002167968,0.0001662345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001321804,0.00681562,0.7099822,0.003393993,0.006897219,0.00006647421,0.1601147,0.007447399,0.03308627,0.01737437,0.007640284,0.04585968],"study_design_scores_gemma":[0.00512016,0.0000101355,0.04382468,0.001822078,0.006975368,0.00005395229,0.000193802,0.7182757,0.07965812,0.03387437,0.1056671,0.004524501],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7957107,0.0004810221,0.1895525,0.001897193,0.0008719402,0.00156675,0.0001673491,0.0001701055,0.009582425],"genre_scores_gemma":[0.8040586,0.000167277,0.1929266,0.0001374036,0.0001408769,0.0003743169,0.0004848239,0.00005766482,0.001652494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7108283,"threshold_uncertainty_score":0.999985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07432530512894601,"score_gpt":0.2707113245029273,"score_spread":0.1963860193739813,"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."}}