{"id":"W4237348302","doi":"10.5194/tcd-8-805-2014","title":"Sea ice melt pond fraction estimation from dual-polarisation C-band SAR – Part 1: In situ observations","year":2014,"lang":"en","type":"preprint","venue":"","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Melt pond; Sea ice; Sea ice thickness; Fetch; Arctic; Arctic ice pack; Surface roughness; Synthetic aperture radar; Environmental science; Geology; Backscatter (email); Remote sensing; Atmospheric sciences; Climatology; Oceanography; Materials science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001839885,0.0003562212,0.0002574305,0.0007511553,0.0001378527,0.0004064816,0.0001535701,0.000218065,0.0005022285],"category_scores_gemma":[0.0002691636,0.0001582842,0.0001803942,0.0005738614,0.0001350701,0.000311477,0.0001867026,0.000108886,0.0002065211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001446044,"about_ca_system_score_gemma":0.0001618545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005367948,"about_ca_topic_score_gemma":0.008488473,"domain_scores_codex":[0.9999375,0.00001058457,0.000004012403,0.00001965815,0.00001621682,0.00001198072],"domain_scores_gemma":[0.9999114,0.00001717034,0.0000175742,0.00001319925,0.00003290955,0.000007800409],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006569627,0.0001729979,0.2228428,0.0002257481,0.0001211544,0.0002566268,0.0002933234,0.03766097,0.6146587,0.0001901749,0.001000623,0.1219199],"study_design_scores_gemma":[0.00004400705,0.0001428614,0.640856,0.00002753428,0.0000948673,0.0002792272,0.0002547162,0.2253638,0.1312934,0.0002202099,0.001386568,0.00003680849],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861254,0.0001314246,0.01188718,0.00001512474,0.000005528947,0.00001588859,0.0004148299,0.0001511119,0.001253466],"genre_scores_gemma":[0.9901455,0.0001238002,0.008508905,0.000009457412,0.000007464745,0.000009541191,0.0008458563,0.00001502838,0.000334561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005367948,"threshold_uncertainty_score":0.0106734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02772895350039421,"score_gpt":0.2352555841983055,"score_spread":0.2075266306979113,"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."}}