{"id":"W2042360192","doi":"10.1007/s10661-014-3995-z","title":"Analysis of multi-temporal landsat satellite images for monitoring land surface temperature of municipal solid waste disposal sites","year":2014,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":77,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; Toronto Metropolitan University","funders":"","keywords":"Environmental science; Satellite; Remote sensing; Municipal solid waste; Satellite imagery; Environmental monitoring; Thematic Mapper; Hydrology (agriculture); Environmental engineering; Waste management; Geology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002652263,0.0002548815,0.0002057946,0.001657652,0.0001966495,0.0004373158,0.0001996216,0.000291257,0.0004850749],"category_scores_gemma":[0.0002713408,0.0001649165,0.0005006102,0.001053436,0.0001023459,0.0002984204,0.0001280066,0.0001294978,0.0001162694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004316801,"about_ca_system_score_gemma":0.0004238943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01593098,"about_ca_topic_score_gemma":0.03268511,"domain_scores_codex":[0.9998989,0.00001066292,0.000009051869,0.0000251406,0.00003547795,0.00002072517],"domain_scores_gemma":[0.9997862,0.00004277861,0.00004845728,0.00001603478,0.0000866816,0.00001988483],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001672381,0.0009045885,0.4685152,0.0002927828,0.0004891738,0.0007412073,0.0003082295,0.06262854,0.3149481,0.0003641143,0.001940296,0.1471954],"study_design_scores_gemma":[0.00001747955,0.00007155707,0.8724678,0.000006752811,0.0001269554,0.0001075759,0.0002026904,0.113371,0.01297774,0.00006520256,0.0005649928,0.000020294],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967706,0.00007515484,0.001682361,0.00001950408,0.000005959971,0.00001085259,0.000882491,0.00003975776,0.0005133387],"genre_scores_gemma":[0.9949892,0.00007488106,0.003087612,0.000006312071,0.000005980003,0.00001012981,0.001336424,0.00001414714,0.0004753731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01593098,"threshold_uncertainty_score":0.03167653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01486686372821008,"score_gpt":0.2657509777102488,"score_spread":0.2508841139820387,"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."}}