{"id":"W1596548499","doi":"10.1002/ppap.201500068","title":"Energy of Reactions in Atmospheric‐Pressure Plasma Polymerization with Inert Carrier Gas","year":2015,"lang":"en","type":"article","venue":"Plasma Processes and Polymers","topic":"Plasma Applications and Diagnostics","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Centre Hospitalier de l’Université de Montréal; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dielectric barrier discharge; Atmospheric pressure; Dopant; Plasma polymerization; Analytical Chemistry (journal); Plasma; Argon; Polymerization; Inert gas; Atmospheric-pressure plasma; Microplasma; Materials science; Inert; Electrode; Plasma cleaning; Chemistry; Dielectric; Atomic physics; Doping; Polymer; Optoelectronics; Organic chemistry; Physical chemistry; Meteorology; Nuclear physics","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":[0.00004849214,0.0001503643,0.0002573275,0.00005093051,0.00004170408,0.00001485932,0.00005364176,0.00009598953,0.00002865429],"category_scores_gemma":[0.0001370029,0.0001220208,0.0000170108,0.0006504757,0.0001150139,0.0001242021,0.00002042564,0.00008774117,0.000001490351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001617756,"about_ca_system_score_gemma":0.0003946046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001076594,"about_ca_topic_score_gemma":0.0003481143,"domain_scores_codex":[0.9991305,0.00001281196,0.0002478866,0.0002230238,0.0001994461,0.0001862942],"domain_scores_gemma":[0.9992143,0.0001277565,0.0001268114,0.0001615002,0.0001604845,0.0002091406],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.01151692,0.004692107,0.6478441,0.006362519,0.001576085,0.0002841498,0.01319307,0.006695449,0.05581405,0.04452857,0.008065198,0.1994278],"study_design_scores_gemma":[0.01799957,0.003463474,0.008027641,0.00154784,0.001482562,0.001336292,0.01017567,0.05754203,0.4818047,0.0005092059,0.4144368,0.001674177],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9858641,0.0019505,0.0008142187,0.001011656,0.00006208268,0.0001905832,0.00006453137,0.00004760936,0.009994735],"genre_scores_gemma":[0.9969563,0.0005629213,0.001107327,0.0001058938,0.00004161385,0.0000568074,0.0000717058,0.00002307063,0.001074357],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6398164,"threshold_uncertainty_score":0.4975865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01132145356543402,"score_gpt":0.2320238516278692,"score_spread":0.2207023980624352,"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."}}