{"id":"W3032682560","doi":"10.5194/tc-14-1595-2020","title":"Combining TerraSAR-X and time-lapse photography for seasonal sea ice monitoring: the case of Deception Bay, Nunavik","year":2020,"lang":"en","type":"article","venue":"The cryosphere","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Glencore (Canada); Kativik Regional Government; Université Laval; Center for Northern Studies; Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada; W. Garfield Weston Foundation; Natural Resources Canada; Ministère des Transports; Institut national de la recherche scientifique; Polar Knowledge Canada","keywords":"Bay; Sea ice; Oceanography; Breakup; Climatology; Series (stratigraphy); Geology; Environmental science; Geography; Physical geography; Remote sensing; Meteorology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007213916,0.0004406165,0.0001720685,0.0008820133,0.001190872,0.001377243,0.001009154,0.0004249037,0.0008469054],"category_scores_gemma":[0.001300839,0.0002141704,0.000199468,0.00158573,0.0006742027,0.0006139193,0.00107317,0.0005472588,0.0001690548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00473425,"about_ca_system_score_gemma":0.003728442,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7951836,"about_ca_topic_score_gemma":0.9176349,"domain_scores_codex":[0.9996124,0.00006649714,0.00002072151,0.00007464036,0.00009618441,0.0001296131],"domain_scores_gemma":[0.9991622,0.0001551942,0.000100002,0.0001372153,0.0002981201,0.0001471908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002982697,0.000206114,0.9363008,0.0001479885,0.0001325596,0.01339646,0.004448303,0.005981438,0.01121784,0.0005951645,0.001451328,0.02582373],"study_design_scores_gemma":[0.00003986488,0.0001057803,0.9506259,0.0001260997,0.00009351409,0.002070255,0.02495363,0.01141727,0.00340106,0.0002305602,0.006877982,0.00005812188],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918088,0.0003164838,0.0005883977,0.0003003544,0.00002081747,0.0000664709,0.0007724427,0.00002912327,0.006097032],"genre_scores_gemma":[0.9966698,0.0001455161,0.001769032,0.00004134334,0.000004094079,0.00001335567,0.0003296114,0.00000975788,0.001017501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2048164,"threshold_uncertainty_score":0.4120452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01482964727450719,"score_gpt":0.2213235478247769,"score_spread":0.2064939005502697,"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."}}