{"id":"W2074502566","doi":"10.1002/mren.200600004","title":"Dynamic Monte Carlo Simulation of ATRP with Bifunctional Initiators","year":2007,"lang":"en","type":"article","venue":"Macromolecular Reaction Engineering","topic":"Advanced Polymer Synthesis and Characterization","field":"Chemistry","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bifunctional; Monte Carlo method; Dispersity; Polymerization; Monomer; Kinetic Monte Carlo; Materials science; Dynamic simulation; Chemistry; Polymer chemistry; Computer science; Polymer; Simulation; Mathematics; Organic chemistry; Catalysis","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006309889,0.0001336541,0.0001238252,0.0001004368,0.00003402832,0.00000903013,0.00004692805,0.00007537074,0.00005824804],"category_scores_gemma":[0.00002280857,0.0001369633,0.00005271112,0.0001544762,0.00001335909,0.0001410305,0.00001047483,0.0001061093,0.000002732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007857671,"about_ca_system_score_gemma":0.00001146916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000103573,"about_ca_topic_score_gemma":0.00000342487,"domain_scores_codex":[0.9992525,0.000003112617,0.00022295,0.0001626086,0.0001991437,0.0001596801],"domain_scores_gemma":[0.9995706,0.00004384851,0.0001199512,0.00015536,0.00005935157,0.00005086191],"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":[0.0000412841,0.00002519395,0.0004050012,0.00004994966,0.00003954793,0.00001136296,0.00004324114,0.2177263,0.7784356,0.00002981986,1.9498e-7,0.003192476],"study_design_scores_gemma":[0.0004144573,0.00002918952,0.00701482,0.0001180246,0.00005282455,0.00004031116,0.00008546781,0.2422423,0.7475053,0.00000400936,0.002193308,0.0002999529],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7334937,0.00005486166,0.2658848,0.000004567843,0.00007281025,0.00002938517,0.00000626892,0.00008310642,0.0003704796],"genre_scores_gemma":[0.998992,0.000006001264,0.0008052506,0.000007174036,0.00004250515,0.000005104782,0.00003050357,0.00003939647,0.00007208294],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2654982,"threshold_uncertainty_score":0.55852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003694181605022742,"score_gpt":0.2057372888288461,"score_spread":0.2020431072238234,"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."}}