{"id":"W6929028113","doi":"10.4224/12327421","title":"Developing an ice strength algorithm for level, landfast first-year sea ice in the High Arctic","year":2003,"lang":"en","type":"report","venue":"NPARC","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; Canadian Wood Council","funders":"","keywords":"Sea ice; Arctic ice pack; Arctic; Cryosphere; Flexural strength; Sea ice thickness","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001225445,0.0005720265,0.0006267614,0.001061072,0.0005439187,0.0008858049,0.001006716,0.0005239442,0.000851164],"category_scores_gemma":[0.003055891,0.0004188193,0.0007242823,0.0005649996,0.0002881089,0.0006824557,0.0004685884,0.0006619986,0.0004272774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009334539,"about_ca_system_score_gemma":0.001962479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01750603,"about_ca_topic_score_gemma":0.0137772,"domain_scores_codex":[0.9997317,0.00004987199,0.00002438009,0.00005525614,0.00009531539,0.00004334536],"domain_scores_gemma":[0.9988669,0.0003428188,0.0001014662,0.00005158734,0.0005926265,0.00004462265],"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":[0.00006252151,0.0000464298,0.0047982,0.00003542394,0.00004095297,0.00006523915,0.00005782338,0.8193663,0.006228492,0.003239919,0.001119351,0.1649392],"study_design_scores_gemma":[0.00000840107,0.000009413016,0.0003361696,0.000002165545,0.000003513132,0.000007933655,0.000006734554,0.9973614,0.001338555,0.0005913361,0.000331576,0.000002865099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03469947,0.00004822065,0.9632995,0.00003059612,0.0000207763,0.00008970334,0.00006227255,0.0008520241,0.0008975075],"genre_scores_gemma":[0.1978391,0.00007394533,0.8003088,0.00002394073,0.0000280315,0.000174601,0.0003887661,0.000145258,0.001017553],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01750603,"threshold_uncertainty_score":0.03480828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0851810280984588,"score_gpt":0.3192823307285517,"score_spread":0.2341013026300929,"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."}}