{"id":"W2979700171","doi":"10.1002/aocs.12290","title":"The Development of Epoxidized Hemp Oil Prepolymers for the Preparation of Thermoset Networks","year":2019,"lang":"en","type":"article","venue":"Journal of the American Oil Chemists Society","topic":"Polymer composites and self-healing","field":"Materials Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Alberta Innovates","keywords":"Thermosetting polymer; Epoxy; Curing (chemistry); Epoxidized soybean oil; Materials science; Polymer; Fourier transform infrared spectroscopy; Monomer; Polymer chemistry; Organic chemistry; Chemistry; Chemical engineering; Raw material","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":[0.001395238,0.0001243515,0.0003289279,0.000005758608,0.0002764514,0.00003786196,0.0007686495,0.00003683086,0.00001008309],"category_scores_gemma":[0.00006321297,0.0000582483,0.0004239268,0.0001573494,0.0003143219,0.00006223108,0.0001143585,0.0001450048,4.638729e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008040657,"about_ca_system_score_gemma":0.0002911635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002818083,"about_ca_topic_score_gemma":0.000003262443,"domain_scores_codex":[0.9984637,0.00007555466,0.0006993892,0.0001214575,0.0004098528,0.0002300356],"domain_scores_gemma":[0.9965376,0.0006686726,0.002187588,0.0003788,0.0001842791,0.00004311845],"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":[0.0002725184,0.00003760328,0.0001852994,0.00005219425,0.0001418962,4.959356e-8,0.003372698,0.001731233,0.9869401,0.000006642783,0.000530953,0.006728783],"study_design_scores_gemma":[0.0004733679,0.00006718081,0.0003288601,0.00008306589,0.00007210528,0.00001415076,0.001801037,0.005369972,0.990325,0.00001530129,0.001355886,0.0000940354],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969539,0.001213821,0.0006524478,0.0005542234,0.0003144047,0.00006286769,0.000004401901,0.000006167193,0.0002377557],"genre_scores_gemma":[0.995191,0.0002624318,0.003791385,0.0001408842,0.0001209537,0.000008473175,6.598989e-7,0.00001350714,0.0004706728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006634748,"threshold_uncertainty_score":0.2375297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008541098723841036,"score_gpt":0.2642027083269168,"score_spread":0.2556616096030758,"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."}}