{"id":"W2093161882","doi":"10.1080/07038992.2000.10874794","title":"Éfficacité des données de RADARSAT-1 dans la reconnaissance des linéaments : un bilan","year":2000,"lang":"fr","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Physics; Cartography; Geography; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0009054659,0.0007762464,0.000443247,0.001056034,0.0004094525,0.001300368,0.0004873459,0.000782794,0.00357387],"category_scores_gemma":[0.001662183,0.0002895118,0.0004764748,0.0008831654,0.00039298,0.0007559007,0.0003575774,0.0004211411,0.0009899499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008827212,"about_ca_system_score_gemma":0.0006450192,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03837783,"about_ca_topic_score_gemma":0.05525125,"domain_scores_codex":[0.9994426,0.00007540957,0.00002330712,0.0001175194,0.0002684413,0.00007267112],"domain_scores_gemma":[0.9991158,0.0002662383,0.00004727993,0.00008241757,0.0004601032,0.00002821911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001402868,0.0001316669,0.01371757,0.0007091115,0.0002534227,0.0003989298,0.0005372561,0.09632657,0.4064013,0.0009765765,0.002255397,0.4768893],"study_design_scores_gemma":[0.0000773765,0.0006664933,0.08491378,0.0001470659,0.0003415268,0.0005901327,0.0009012204,0.5222507,0.3721766,0.0009062701,0.01691366,0.0001152182],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8230364,0.002164626,0.1582936,0.0005120949,0.0001523734,0.0001564138,0.001037359,0.002868989,0.01177807],"genre_scores_gemma":[0.9167483,0.0008024769,0.07288243,0.0001034318,0.00002521151,0.00005682282,0.0009258995,0.0001856092,0.008269769],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03837783,"threshold_uncertainty_score":0.07630885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03210534028057292,"score_gpt":0.2404108999496903,"score_spread":0.2083055596691174,"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."}}