{"id":"W2018971020","doi":"10.1016/s0014-3057(01)00181-1","title":"Real-time mid-IR monitoring of metathesis reactions by fiber optic FTIR spectroscopy","year":2002,"lang":"en","type":"article","venue":"European Polymer Journal","topic":"Synthetic Organic Chemistry Methods","field":"Chemistry","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Ring-opening metathesis polymerisation; Polymerization; Phenylacetylene; ROMP; Metathesis; Monomer; Absorbance; Materials science; Polymer chemistry; Precipitation polymerization; Grubbs' catalyst; Fourier transform infrared spectroscopy; Photochemistry; Chemistry; Polymer; Catalysis; Organic chemistry; Chemical engineering; Radical polymerization; Composite material; Chromatography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003952252,0.000470279,0.000250005,0.0003086634,0.0002641623,0.0002912543,0.0004186328,0.0004879648,0.001362129],"category_scores_gemma":[0.000465797,0.0002277293,0.0001896102,0.0002990197,0.0002389804,0.0007093043,0.0001750841,0.0008278839,0.0003757997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002645883,"about_ca_system_score_gemma":0.0001915613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003714864,"about_ca_topic_score_gemma":0.0005650904,"domain_scores_codex":[0.9997581,0.00003763679,0.000009260549,0.00006294208,0.00008564147,0.00004632284],"domain_scores_gemma":[0.9997755,0.00007784727,0.00005468357,0.00002459287,0.00004391782,0.00002349624],"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":[0.0001735333,0.00001746952,0.00007938274,0.00001128879,0.000002912217,0.000011445,0.00001391383,0.00005975461,0.9982501,0.00004165148,0.0000247206,0.001313906],"study_design_scores_gemma":[0.00000462252,0.00009940915,0.0006382936,9.923134e-7,0.000003793048,0.00002978724,0.000007127684,0.0007795417,0.9982014,0.0000191097,0.0002130572,0.000002879504],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9750028,0.0009608867,0.02057839,0.0001055535,0.00006436143,0.00004600595,0.0004640223,0.0003202137,0.002457762],"genre_scores_gemma":[0.9804186,0.0006430284,0.01577786,0.00004855877,0.00001815145,0.00005572964,0.0004133885,0.00005555362,0.002569091],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001362129,"threshold_uncertainty_score":0.004556715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02043089615396835,"score_gpt":0.2610635419731663,"score_spread":0.240632645819198,"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."}}