{"id":"W2361868492","doi":"","title":"Research of the Application Ability of Using CCD Multi-spectral Data of NO.1 Environment Satellite in 1:250 000 Topographic Map Update","year":2011,"lang":"en","type":"article","venue":"Geomatics & Spatial Information Technology","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation Initiatives Ontario North","funders":"","keywords":"Satellite; Remote sensing; Feature (linguistics); Computer science; Satellite imagery; Artificial intelligence; Computer vision; Geography; Physics","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":[0.0008497642,0.0002169921,0.0001764446,0.0009739185,0.000192067,0.0004200223,0.00034204,0.0003653232,0.0008739142],"category_scores_gemma":[0.002273187,0.0001306473,0.0002365213,0.0008165995,0.0001547212,0.001053482,0.0002399533,0.0002341035,0.0002333542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002055154,"about_ca_system_score_gemma":0.0001956256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002662903,"about_ca_topic_score_gemma":0.002779958,"domain_scores_codex":[0.9994691,0.0001244069,0.00001960047,0.000107297,0.0002335312,0.00004605576],"domain_scores_gemma":[0.9989942,0.0002970874,0.00006043398,0.00009589016,0.0005155577,0.00003689829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003625845,0.0001131505,0.07431901,0.0005029104,0.00006514168,0.000394996,0.0009245093,0.01186156,0.1444875,0.001974375,0.00233711,0.762657],"study_design_scores_gemma":[0.00006148175,0.001077893,0.3338757,0.0001266612,0.0005004964,0.002621142,0.002321679,0.2146531,0.38902,0.002568885,0.05301861,0.000154416],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8706189,0.002933169,0.1139156,0.0004553696,0.000130928,0.00008050371,0.0002480691,0.0003828337,0.0112345],"genre_scores_gemma":[0.9537424,0.001446048,0.04218281,0.00003997468,0.0000681241,0.00001888131,0.0001989082,0.00003371728,0.002269121],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002662903,"threshold_uncertainty_score":0.0052948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06592309663028913,"score_gpt":0.2784333322942353,"score_spread":0.2125102356639462,"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."}}