{"id":"W3120158035","doi":"10.5194/tc-15-2803-2021","title":"An improved sea ice detection algorithm using MODIS: application as a new European sea ice extent indicator","year":2021,"lang":"en","type":"article","venue":"The cryosphere","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Universitat Autònoma de Barcelona","keywords":"Sea ice; Arctic ice pack; Climatology; Cryosphere; Northern Hemisphere; Arctic; Environmental science; Sea ice concentration; Geology; Oceanography; Remote sensing; Sea ice thickness","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":[0.001647517,0.0007573182,0.0004324235,0.001812722,0.000185301,0.0007691705,0.0003775038,0.0003601954,0.0006423637],"category_scores_gemma":[0.001085287,0.0001556831,0.0003831932,0.001813019,0.0001545018,0.0005057522,0.0005133467,0.0001814248,0.0003521222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003962285,"about_ca_system_score_gemma":0.0004177878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006901253,"about_ca_topic_score_gemma":0.005817262,"domain_scores_codex":[0.9994692,0.00008557689,0.00005416644,0.0001838715,0.0001687894,0.00003832385],"domain_scores_gemma":[0.9995298,0.00006166998,0.00006754113,0.00007160546,0.0002289535,0.00004027238],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001493065,0.0005849104,0.1280695,0.0006898262,0.0005452017,0.0006693049,0.0003408955,0.145228,0.1289276,0.001781516,0.01945587,0.5722142],"study_design_scores_gemma":[0.0001621827,0.0002570334,0.2076727,0.0001133332,0.0001496524,0.0003022119,0.0001649366,0.6975884,0.06256331,0.0006414899,0.03025686,0.0001278764],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8020256,0.001147952,0.1676733,0.0002096234,0.0002627985,0.0003275787,0.01786948,0.004420538,0.006063095],"genre_scores_gemma":[0.6149769,0.0004733859,0.3593952,0.0001084946,0.0000519684,0.0002777089,0.02238486,0.0002837921,0.002047829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006901253,"threshold_uncertainty_score":0.01372218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008951733304356438,"score_gpt":0.2175457449159775,"score_spread":0.2085940116116211,"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."}}