{"id":"W4391786450","doi":"10.46873/2300-3960.1403","title":"A quick and cost-effective method for monitoring deforestation of oil sands mining activities using Synthetic Aperture Radar and Multispectral real-time satellite data from Sentinel-1 and Sentinel-2.","year":2024,"lang":"en","type":"article","venue":"Journal of Sustainable Mining","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multispectral image; Remote sensing; Synthetic aperture radar; Satellite; Radar; Geology; Environmental science; Computer science; Engineering; Telecommunications; Aerospace engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001257457,0.0001779279,0.0003668263,0.0001812544,0.0001803921,0.0003108702,0.0002096219,0.00008678016,0.000001638996],"category_scores_gemma":[0.0005989969,0.0001565284,0.00004389061,0.0001965534,0.0000717126,0.001038997,0.0003322015,0.0001659752,3.192166e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005506557,"about_ca_system_score_gemma":0.0001065205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005420182,"about_ca_topic_score_gemma":8.167951e-7,"domain_scores_codex":[0.9986636,0.0001111189,0.000372001,0.0003646899,0.0001749056,0.0003136742],"domain_scores_gemma":[0.9970645,0.002144566,0.0003194155,0.0001920897,0.0001889838,0.00009046668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006864722,0.0001358034,0.03320563,0.007175468,0.001144342,0.001438454,0.06733518,0.001827568,0.5572027,0.001339337,0.000201646,0.3283074],"study_design_scores_gemma":[0.001199627,0.0001425044,0.004654098,0.001848099,0.0002649144,0.0008815281,0.03102724,0.9448504,0.01178063,0.001219569,0.001776913,0.0003544168],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9200351,0.003344518,0.07585258,0.0003412671,0.00008981185,0.0001628602,0.000008860428,0.00002240036,0.0001426103],"genre_scores_gemma":[0.7918607,0.000376863,0.2071922,0.00001025771,0.0001881929,0.000007830427,0.000006154837,0.0000108248,0.0003470505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9430229,"threshold_uncertainty_score":0.6383042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02427104563610758,"score_gpt":0.3028152587710459,"score_spread":0.2785442131349383,"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."}}