{"id":"W2164783694","doi":"10.5194/bg-8-121-2011","title":"Formation and global distribution of sea-surface microlayers","year":2011,"lang":"en","type":"article","venue":"Biogeosciences","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":315,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"Office of Naval Research; Fisheries and Oceans Canada; Deutsche Forschungsgemeinschaft; ArcticNet","keywords":"Environmental science; Oceanography; Trophic level; Wind speed; Subtropics; Atmosphere (unit); Atmospheric sciences; Temperate climate; Climatology; Geology; Meteorology; Geography; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001842392,0.00004919082,0.00006549316,0.00001052365,0.00007431195,0.00002009737,0.0001019422,0.00002324708,0.0001504165],"category_scores_gemma":[0.00001361724,0.00003625735,0.00001699555,0.0002089893,0.00009885802,0.0002998657,0.00001173476,0.00001527576,0.0000183174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000178282,"about_ca_system_score_gemma":0.00001887057,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03140448,"about_ca_topic_score_gemma":0.007296646,"domain_scores_codex":[0.9995129,0.0000199493,0.0001182842,0.0001052059,0.0001236995,0.0001199222],"domain_scores_gemma":[0.9997913,0.00001227251,0.00006583046,0.00005451843,0.00002292921,0.00005314007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009373832,0.000005030963,0.9703408,0.00001240956,0.00000109502,6.740668e-7,0.00007121218,0.000002049291,0.0000834946,0.0001783615,0.0001101785,0.02918531],"study_design_scores_gemma":[0.00006625678,0.0001284586,0.9909257,0.000007457238,0.000004230923,0.00002108285,0.0003409557,0.004155499,0.00172418,0.000500192,0.002056492,0.00006949452],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866377,0.0002007927,0.0002314019,0.0000247981,0.0001335645,0.00005845577,0.0003146667,0.0000119891,0.0123867],"genre_scores_gemma":[0.9996107,0.00003486945,0.0002606509,0.00001492125,0.000008626824,1.2113e-7,0.00004881576,2.530852e-7,0.00002100749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02911581,"threshold_uncertainty_score":0.9750455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01731558907123963,"score_gpt":0.1925814450373919,"score_spread":0.1752658559661522,"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."}}