{"id":"W3030271920","doi":"","title":"Canadian plans for Thematic Mapper data","year":2011,"lang":"en","type":"article","venue":"","topic":"Satellite Image Processing and Photogrammetry","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digital data; Remote sensing; Thematic Mapper; Computer science; Data format; Data quality; Pixel; Telecommunications; Database; Data transmission; Geography; Computer hardware; Engineering; Satellite imagery; Artificial intelligence","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":[0.002103036,0.0008446089,0.0005113427,0.006279462,0.003710042,0.002990403,0.002377644,0.000584243,0.05883017],"category_scores_gemma":[0.004840767,0.0005420191,0.001077097,0.01161107,0.0003870643,0.001203953,0.001587595,0.001574737,0.01207473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02586246,"about_ca_system_score_gemma":0.08850824,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9811082,"about_ca_topic_score_gemma":0.9853753,"domain_scores_codex":[0.9977877,0.0001298779,0.00007052952,0.0001570623,0.001488677,0.0003660659],"domain_scores_gemma":[0.9922861,0.0001229439,0.000117536,0.0003736924,0.006605862,0.0004937583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009745998,0.000040898,0.005676236,0.0003434333,0.00004610075,0.0001078936,0.0002951899,0.002099735,0.001108816,0.02416313,0.8579809,0.1080402],"study_design_scores_gemma":[0.00003284141,0.000009677022,0.01424381,0.0001227885,0.00002410055,0.00004322962,0.0003909192,0.002922233,0.0006732217,0.001864342,0.979632,0.00004104203],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.00559057,0.0009314062,0.01819274,0.005583504,0.0007111375,0.001327006,0.7046818,0.003110422,0.2598714],"genre_scores_gemma":[0.0526686,0.002559265,0.1414216,0.001448748,0.0001402263,0.001645339,0.5884959,0.002285568,0.2093349],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05883017,"threshold_uncertainty_score":0.1968066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1009855389123313,"score_gpt":0.2453907670239805,"score_spread":0.1444052281116492,"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."}}