{"id":"W2757758330","doi":"10.1021/acs.chemmater.7b03674","title":"Patterned Phosphonium-Functionalized Photopolymer Networks as Ceramic Precursors","year":2017,"lang":"en","type":"article","venue":"Chemistry of Materials","topic":"Advanced Polymer Synthesis and Characterization","field":"Chemistry","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Research and Innovation Foundation; Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science; Canada Foundation for Innovation","keywords":"Materials science; Phosphonium; Thermogravimetric analysis; Scanning electron microscope; X-ray photoelectron spectroscopy; Surface modification; Photopolymer; Polymer; Differential scanning calorimetry; Chemical engineering; Ceramic; Infrared spectroscopy; Polymer chemistry; Polymerization; Organic chemistry; Composite material; Chemistry","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00008804439,0.0002528244,0.0004050856,0.000008910313,0.0002490131,0.0001318911,0.0004844487,0.0002351042,0.0387324],"category_scores_gemma":[0.00009552509,0.0002533532,0.0001025728,0.00001646505,0.0001751345,0.0001787043,0.0001207501,0.00008209779,0.00003285758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003307627,"about_ca_system_score_gemma":0.00003686312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007589842,"about_ca_topic_score_gemma":4.049277e-7,"domain_scores_codex":[0.9987146,0.0000107582,0.0004472808,0.0003516347,0.0002051689,0.000270506],"domain_scores_gemma":[0.998176,0.00003822991,0.0007744566,0.0008613009,0.00006277031,0.0000871813],"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":[0.0002240062,0.00006155681,0.0004659515,0.0002267347,0.00005952307,0.000003584667,0.00003704983,0.000005693872,0.9969516,0.00001500402,0.00007725101,0.001871987],"study_design_scores_gemma":[0.0006149606,0.000005117456,0.0004847898,0.000156421,0.00004144216,0.00001095492,0.00003566712,0.00001949595,0.9956703,0.000106621,0.002596957,0.000257246],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850136,0.0002505137,0.0001058823,0.00006916604,0.0004274182,0.00005465875,0.0001331139,0.0000646163,0.01388104],"genre_scores_gemma":[0.987641,0.0001373332,0.00003646894,0.00003794876,0.0004863253,0.00004839023,0.0002463516,0.00004593743,0.01132025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03869954,"threshold_uncertainty_score":0.9999919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009849155083321121,"score_gpt":0.2420517843642928,"score_spread":0.2322026292809717,"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."}}