{"id":"W4415269351","doi":"10.2139/ssrn.5616763","title":"Knowledge-Aware Mamba for Joint Change Detection and Classification from MODIS Times Series","year":2025,"lang":"","type":"preprint","venue":"SSRN Electronic Journal","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Change detection; Leverage (statistics); Series (stratigraphy); Joint (building); Time series","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009072052,0.0008480622,0.001341261,0.0008280713,0.0004753259,0.001089552,0.001446654,0.001020846,0.002122945],"category_scores_gemma":[0.002845278,0.0004617051,0.0009929835,0.0009337754,0.0002930712,0.001298636,0.001216065,0.001392913,0.001421681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005085694,"about_ca_system_score_gemma":0.0009417075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01050243,"about_ca_topic_score_gemma":0.0151028,"domain_scores_codex":[0.9996942,0.00005592837,0.00002064967,0.0001188455,0.00005945232,0.00005098424],"domain_scores_gemma":[0.9994996,0.0002373153,0.00003880459,0.00009726704,0.00009953568,0.00002748699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001006633,0.0004102125,0.004440978,0.0002916072,0.0003595031,0.0001677092,0.0001440049,0.2293936,0.03031291,0.005034503,0.01188585,0.7165524],"study_design_scores_gemma":[0.00001186977,0.00002353954,0.0007943052,0.000006541385,0.00002152054,0.00001908756,0.00002243967,0.9913886,0.002610256,0.00408269,0.001010256,0.00000899915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05899181,0.001082406,0.9260707,0.0004441753,0.0002025419,0.0001031153,0.001936727,0.009520554,0.00164805],"genre_scores_gemma":[0.6191616,0.0004157127,0.3716674,0.0002879907,0.0002105556,0.0002474804,0.005014498,0.0003174748,0.002677288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01050243,"threshold_uncertainty_score":0.02088261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04113975938355358,"score_gpt":0.2662303830868895,"score_spread":0.2250906237033359,"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."}}