{"id":"W3017016299","doi":"10.1016/j.aeaoa.2020.100072","title":"Mapping the deposition of <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si1.svg\"> <mml:mrow> <mml:mmultiscripts> <mml:mtext>C</mml:mtext> <mml:mprescripts/> <mml:none/> <mml:mn>137</mml:mn> </mml:mmultiscripts> <mml:mtext>s</mml:mtext> </mml:mrow> </mml:math> and <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si2.svg\"> <mml:mrow> <mml:mmultiscripts> <mml:mtext>I</mml:mtext> <mml:mprescripts/> <mml:none/> <mml:mn>131</mml:mn> </mml:mmultiscripts> </mml:mrow> </mml:math> in North America following the 2011 Fukushima Daiichi Reactor accident","year":2020,"lang":"lv","type":"article","venue":"Atmospheric Environment X","topic":"Radioactive contamination and transfer","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Health Canada","funders":"","keywords":"Context (archaeology); Deposition (geology); Nuclear explosion; Algorithm; Computer science; Environmental science; Meteorology; Physics; Geology; Nuclear 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":["metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"category_scores_codex":[0.004880428,0.00415824,0.001945142,0.0007506659,0.005593255,0.003942068,0.007697666,0.005196323,0.08513639],"category_scores_gemma":[0.002287181,0.006143683,0.005314341,0.003307097,0.006577663,0.006559101,0.006460682,0.006607839,0.008072193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003139612,"about_ca_system_score_gemma":0.002035697,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0128813,"about_ca_topic_score_gemma":0.006425914,"domain_scores_codex":[0.9688257,0.002439288,0.006772335,0.006891654,0.007871996,0.007199],"domain_scores_gemma":[0.979401,0.003255082,0.006233608,0.007295213,0.0003418948,0.003473188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006546372,0.003908936,0.0007069487,0.003460546,0.009651033,0.006392351,0.02505217,0.01327705,0.05286525,0.6966456,0.1516653,0.02982846],"study_design_scores_gemma":[0.009253578,0.004869633,0.004910509,0.003239592,0.006030385,0.002583925,0.01549243,0.5197095,0.3826326,0.0001609763,0.04398659,0.007130214],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.890802,0.008353482,0.005851157,0.002951046,0.007539036,0.0007115246,0.001753952,0.0008910209,0.08114681],"genre_scores_gemma":[0.9585503,0.01024787,0.009419287,0.006877739,0.002828681,0.004611842,0.003708452,0.002457548,0.001298277],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6964846,"threshold_uncertainty_score":0.9976712,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01972513670243166,"score_gpt":0.2224113926925449,"score_spread":0.2026862559901133,"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."}}