{"id":"W2946935961","doi":"10.1016/j.coldregions.2019.102955","title":"An open source, versatile, affordable waves in ice instrument for scientific measurements in the Polar Regions","year":2019,"lang":"en","type":"preprint","venue":"Cold Regions Science and Technology","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"Norges Forskningsråd","keywords":"Sea ice; Remote sensing; Scientific instrument; Computer science; Open source; Polar; Environmental science; Geology; Meteorology; Geography; Software; Oceanography; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002971825,0.0002191555,0.0003078492,0.001024213,0.0009713508,0.0006111473,0.003092507,0.0002803955,0.00001542765],"category_scores_gemma":[0.0002298131,0.0001618586,0.00003035168,0.001995351,0.002337695,0.000547107,0.0004842944,0.0005588094,0.0000108882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006017471,"about_ca_system_score_gemma":0.001128135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002846874,"about_ca_topic_score_gemma":0.01167267,"domain_scores_codex":[0.9975091,0.00007627882,0.0003114134,0.0009241005,0.0005165829,0.0006625782],"domain_scores_gemma":[0.9984457,0.0001156894,0.0001780939,0.0009969354,0.0001767836,0.00008678294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007989413,0.0003883506,0.9220801,0.0001840269,0.00002901039,0.00001568014,0.003877662,0.005564496,0.0006371925,0.0412023,0.001685398,0.0242559],"study_design_scores_gemma":[0.005311298,0.002692363,0.2097334,0.001730498,0.0002092345,0.0002346545,0.07245544,0.3433235,0.0005861039,0.2219581,0.1388695,0.002895965],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9822901,0.0002653425,0.001285955,0.01025897,0.0008081644,0.002865786,0.00007873501,0.0000565085,0.002090442],"genre_scores_gemma":[0.996978,0.0001083659,0.002198673,0.000291687,0.00001919613,0.00005239939,0.00006130316,0.000005579497,0.0002848345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7123467,"threshold_uncertainty_score":0.8613335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04819593857257044,"score_gpt":0.2630204029680014,"score_spread":0.214824464395431,"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."}}