{"id":"W23672439","doi":"10.1111/his.12143","title":"Mapping Pre-Fire Forest Conditions with NOAA-AVHRR Images in the Northwest Territories, Canada","year":2002,"lang":"en","type":"article","venue":"Histopathology","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Forestry; Phone; Meteorology; Remote sensing; Physical geography; Cartography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001982757,0.0002371577,0.000175984,0.001076055,0.001582433,0.0007470951,0.0004998049,0.0003100492,0.0008139202],"category_scores_gemma":[0.0004663579,0.0001586155,0.0001240542,0.001399077,0.0004396994,0.0001977872,0.0002359031,0.0002666255,0.00018575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007095892,"about_ca_system_score_gemma":0.006723878,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9914334,"about_ca_topic_score_gemma":0.99735,"domain_scores_codex":[0.9998119,0.0000131554,0.000007792295,0.00002430122,0.00006670899,0.00007607501],"domain_scores_gemma":[0.9995742,0.0000240748,0.00003019985,0.00001393731,0.0002735592,0.00008397277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004425283,0.0001467067,0.9301472,0.0001126455,0.0001275217,0.002979842,0.001673648,0.0027147,0.01663863,0.0003233138,0.003390588,0.04130267],"study_design_scores_gemma":[0.000005898184,0.00001076866,0.9953331,0.00001397659,0.00001829027,0.0002467068,0.001355671,0.0008501611,0.0006712558,0.00002206888,0.001461602,0.00001050964],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925171,0.0004578982,0.0002466915,0.0001521461,0.00000933042,0.00003980799,0.001813871,0.00002542037,0.004737717],"genre_scores_gemma":[0.9969401,0.0003004569,0.0006384624,0.00003138214,0.000003716721,0.000005879626,0.0005645903,0.000006089004,0.001509303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008566618,"threshold_uncertainty_score":0.05148453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007287799779761075,"score_gpt":0.1890289355673723,"score_spread":0.1817411357876112,"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."}}