{"id":"W4252214712","doi":"10.5194/tc-2018-24","title":"What historical landfast ice observations tell us about projected ice conditions in Arctic Archipelagoes and marginal seas under anthropogenic forcing","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"GDG Environnement; Environment and Climate Change Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sea ice; Arctic ice pack; Archipelago; Antarctic sea ice; Geology; Drift ice; Ice shelf; Climatology; Fast ice; Arctic; Oceanography; Cryosphere","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":[0.0005656343,0.0001844154,0.0001240517,0.0004876126,0.0002098269,0.0009018097,0.0002713147,0.0004110707,0.0009221915],"category_scores_gemma":[0.002356041,0.0001852929,0.0002926248,0.0006887974,0.0002984181,0.0008134712,0.0002186374,0.0002768985,0.0001915491],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008258176,"about_ca_system_score_gemma":0.0003473134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06758095,"about_ca_topic_score_gemma":0.1189084,"domain_scores_codex":[0.9999141,0.00002002903,0.000005409928,0.00002819397,0.00001456417,0.0000178032],"domain_scores_gemma":[0.9992197,0.0002303623,0.0001953645,0.00007759593,0.000179267,0.00009776302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005127016,0.00001018508,0.9899045,0.00001895202,0.00008566352,0.00004538825,0.0001192553,0.006242165,0.0004428581,0.0001225694,0.0002465746,0.002710543],"study_design_scores_gemma":[0.000002568395,0.00001310556,0.9917904,0.00001502482,0.00002263627,0.00002605567,0.0003177093,0.006872683,0.0002487589,0.0001470624,0.0005351343,0.000008920631],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973722,0.0001561753,0.0001873879,0.00008923638,0.000005698948,0.000001418042,0.00147032,0.00001092266,0.0007066345],"genre_scores_gemma":[0.9984967,0.0001267597,0.00009938982,0.00001349065,0.000004386389,0.000001338249,0.001159362,0.00000327105,0.00009538566],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06758095,"threshold_uncertainty_score":0.1343752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03412760844281572,"score_gpt":0.2559952336356237,"score_spread":0.2218676251928079,"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."}}