{"id":"W2149534170","doi":"10.1002/masy.200450239","title":"Process modelling and optimization of styrene polymerization","year":2004,"lang":"en","type":"article","venue":"Macromolecular Symposia","topic":"Thermal and Kinetic Analysis","field":"Materials Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Polystyrene; Bifunctional; Styrene; Polymerization; Materials science; Process (computing); Process engineering; Polymer chemistry; Computer science; Copolymer; Polymer; Chemistry; Catalysis; Organic chemistry; Composite material; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004372821,0.0009852161,0.0009338729,0.0005197523,0.0003852918,0.001236075,0.000688018,0.001312365,0.004350607],"category_scores_gemma":[0.0008577311,0.0004596048,0.0009164866,0.0004862582,0.0004267779,0.0005874937,0.0003583999,0.0006549075,0.0008586662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009776903,"about_ca_system_score_gemma":0.001049108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009407304,"about_ca_topic_score_gemma":0.003431482,"domain_scores_codex":[0.9997805,0.00004856609,0.00001102456,0.00004596163,0.00007095152,0.00004297001],"domain_scores_gemma":[0.9996137,0.0002067403,0.00005499424,0.00002519838,0.00008192696,0.00001731891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001176306,0.00001224986,0.00009215573,0.00002331418,0.000003916725,0.00001380653,0.000006059884,0.9965097,0.001113882,0.001021062,0.00006406372,0.001127937],"study_design_scores_gemma":[0.00000274755,0.000006481113,0.00003597007,0.000001589129,0.000001681228,0.000001947703,0.00000154341,0.9988,0.0005852056,0.0002988749,0.0002624037,0.000001487526],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2909731,0.002142417,0.6490185,0.0005284517,0.0001501615,0.0002771638,0.001418127,0.001476849,0.05401533],"genre_scores_gemma":[0.9615797,0.0007059904,0.02540126,0.00003002965,0.00001643085,0.0002799425,0.0005038981,0.0001647415,0.011318],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009407304,"threshold_uncertainty_score":0.01870513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005267369231719721,"score_gpt":0.2082080413977969,"score_spread":0.2029406721660771,"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."}}