{"id":"W4213305934","doi":"10.1002/cjce.24386","title":"Using poly(acrylamide‐co‐lauric acid) to remediate oil spills on water","year":2022,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Oil Spill Detection and Mitigation","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Lauric acid; Acrylamide; Oil spill; Copolymer; Seawater; Polymer; Environmental remediation; Asphalt; Materials science; Contamination; Chemical engineering; Environmental science; Chemistry; Organic chemistry; Composite material; Environmental engineering; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002988076,0.00008339371,0.00008949314,0.00009243767,0.000156188,0.0000266993,0.0002223963,0.00002421503,0.001119348],"category_scores_gemma":[0.00005511415,0.00006077728,0.00005724751,0.0001712423,0.00002841351,0.00006293415,0.0000335669,0.0003202801,0.00005746464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008036998,"about_ca_system_score_gemma":0.00003482128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001055929,"about_ca_topic_score_gemma":0.000155317,"domain_scores_codex":[0.999193,0.0000173956,0.0001773049,0.00008284446,0.0002620553,0.0002674743],"domain_scores_gemma":[0.9994717,0.00001413632,0.0000391927,0.0001012591,0.000007162052,0.0003665299],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000008030714,0.000003564969,0.00007911642,0.000002231488,0.000006842564,0.00002531495,0.0003800307,0.0995647,0.8958542,0.00001229361,0.0003266484,0.003737063],"study_design_scores_gemma":[0.0001951004,0.0000645339,0.0002481402,0.00001660534,0.00001263093,0.0001957551,0.00002772203,0.003874963,0.9737023,0.0000501748,0.02145355,0.0001585792],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978063,0.0000330868,0.00008828994,0.001042218,0.0003580075,0.00002608218,0.000003380422,0.000008289537,0.0006344107],"genre_scores_gemma":[0.9988955,5.230025e-7,0.000257067,0.0005943109,0.000125137,0.000002461038,9.139006e-7,0.00001525943,0.0001087932],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09568974,"threshold_uncertainty_score":0.9997938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01003504232559793,"score_gpt":0.1939498823508154,"score_spread":0.1839148400252175,"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."}}