{"id":"W2323262238","doi":"10.1109/jstars.2013.2292795","title":"Sea Ice Surface Temperature Estimation Using MODIS and AMSR-E Data Within a Guided Variational Model Along the Labrador Coast","year":2014,"lang":"en","type":"article","venue":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Aeronautics and Space Administration","keywords":"Sea ice concentration; Moderate-resolution imaging spectroradiometer; Remote sensing; Sea surface temperature; Sea ice; Sea ice thickness; Geology; Environmental science; Pixel; Surface (topology); Climatology; Meteorology; Arctic ice pack; Computer science; Geometry; Satellite; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003857487,0.0005122218,0.0003130611,0.0003474685,0.0002433679,0.00058389,0.0007319106,0.0004851274,0.0002863202],"category_scores_gemma":[0.0006136783,0.0002881468,0.0005744754,0.0003930306,0.0002487203,0.0006616669,0.0004476219,0.0004097139,0.0001000704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004529289,"about_ca_system_score_gemma":0.0008944788,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05024583,"about_ca_topic_score_gemma":0.06672403,"domain_scores_codex":[0.9998521,0.00004330029,0.000005243522,0.00004675386,0.00002426246,0.00002830958],"domain_scores_gemma":[0.9999117,0.00002341247,0.00001648744,0.00001202454,0.00002571431,0.00001070101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001896769,0.00009909695,0.02472557,0.00005155374,0.0001716951,0.0001113801,0.0001210955,0.8763812,0.009626844,0.002401192,0.0008876173,0.08523298],"study_design_scores_gemma":[0.000003325748,0.000009154154,0.002233071,0.000002135424,0.000007509664,0.000006133822,0.00001620982,0.9968183,0.0005136475,0.0001886373,0.0001963183,0.000005537236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7173755,0.0004853849,0.2785546,0.0002537683,0.00004869662,0.00002866603,0.0003977784,0.0003134164,0.002542176],"genre_scores_gemma":[0.9405459,0.0001502935,0.05696924,0.00003839402,0.00001644969,0.00002424739,0.0004703935,0.00003721309,0.001747921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9497542,"threshold_uncertainty_score":0.09990674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0374133875429879,"score_gpt":0.2404623200305648,"score_spread":0.2030489324875769,"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."}}