{"id":"W2127627170","doi":"10.1111/j.2041-210x.2011.00161.x","title":"State‐space framework for estimating measurement error from double‐tagging telemetry experiments","year":2011,"lang":"en","type":"article","venue":"Methods in Ecology and Evolution","topic":"Avian ecology and behavior","field":"Environmental Science","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Office of Naval Research; U.S. Navy; U.S. Fish and Wildlife Service; California Department of Fish and Game; Alaska Department of Fish and Game; National Park Service; Massachusetts Department of Fish and Game; National Marine Fisheries Service; Alfred P. Sloan Foundation; U.S. Department of the Interior","keywords":"Geolocation; Telemetry; Geographic coordinate system; Computer science; Satellite; Range (aeronautics); Remote sensing; Longitude; Accuracy and precision; Ranging; Location data; Data mining; Latitude; Statistics; Real-time computing; Geography; Cartography; Geodesy; Mathematics; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001635063,0.0001366163,0.0002021746,0.00005523649,0.0002310469,0.000005837013,0.0001224488,0.0002366464,0.000669152],"category_scores_gemma":[0.0002834532,0.000135889,0.00003290328,0.0001151621,0.0002029628,0.0001606482,0.0001248611,0.0002170467,0.00003206706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003778645,"about_ca_system_score_gemma":0.00001427521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000212648,"about_ca_topic_score_gemma":0.0005140099,"domain_scores_codex":[0.9986343,0.0002831625,0.0002577902,0.0003740944,0.00009163168,0.0003589792],"domain_scores_gemma":[0.9994298,0.0002218682,0.0001233329,0.000151106,0.00001065136,0.00006326349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001229638,0.0001513893,0.9847247,0.000005015715,0.00001263923,0.000002770539,0.001377014,0.0001400707,0.004034573,0.0002195953,0.00005341367,0.009155841],"study_design_scores_gemma":[0.0006565748,0.0001530731,0.9495434,0.00001556922,0.00002873269,0.000002470893,0.0003640302,0.001954839,0.006071553,0.04099525,0.00005909163,0.0001554044],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.502381,0.0000636406,0.4965039,0.00004887802,0.0004902173,0.0002583633,0.000002155275,0.00002237059,0.0002294924],"genre_scores_gemma":[0.4667809,0.000001409195,0.5329897,0.00006652668,0.00001669514,0.0001110115,0.000001370943,0.000006462617,0.00002589752],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.04077565,"threshold_uncertainty_score":0.7326745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1119867787904186,"score_gpt":0.3855713473414576,"score_spread":0.2735845685510391,"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."}}