{"id":"W2046711282","doi":"10.1002/masy.200851106","title":"Estimating Reactivity Ratios From Triad Fraction Data","year":2008,"lang":"en","type":"article","venue":"Macromolecular Symposia","topic":"Process Optimization and Integration","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Triad (sociology); Reactivity (psychology); Fraction (chemistry); Copolymer; Composition (language); Thermodynamics; Multiplicative function; Mole fraction; Chemistry; Statistics; Mathematics; Materials science; Organic chemistry; Mathematical analysis; Physics; Polymer","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":[0.00008700349,0.0001429717,0.0001478463,0.00005456467,0.0001283153,0.00005665452,0.0002319747,0.00008674839,0.00008916439],"category_scores_gemma":[0.00009965627,0.0001530398,0.00003068362,0.0001623026,0.00002020716,0.0006227168,0.00004269099,0.0001605624,0.00008225578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000587987,"about_ca_system_score_gemma":0.00002734829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008968764,"about_ca_topic_score_gemma":0.00001281228,"domain_scores_codex":[0.9991782,0.00003494238,0.0002137954,0.0002520622,0.0001788273,0.0001421757],"domain_scores_gemma":[0.9993002,0.0000292115,0.00004998962,0.00052106,0.00004414988,0.00005536598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004449638,0.0001381144,0.0009879681,0.00005223668,0.000182045,0.0001298879,0.0006967111,0.2014857,0.7628172,0.000414958,0.01147516,0.02157553],"study_design_scores_gemma":[0.0003005169,0.00001178359,0.0005560457,0.0000200487,0.00001942669,0.00002450465,0.000009855531,0.9473711,0.04696913,0.00008157154,0.004456679,0.0001794011],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1561779,0.0002667778,0.8380979,0.00006170997,0.0003536326,0.0001398513,0.000045413,0.000434622,0.004422185],"genre_scores_gemma":[0.9612395,0.00007315396,0.0374104,0.00008696185,0.0001497871,0.00001546551,0.0009496692,0.00003657562,0.00003845507],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8050616,"threshold_uncertainty_score":0.6240782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02283383270301163,"score_gpt":0.2435673211285537,"score_spread":0.2207334884255421,"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."}}