{"id":"W2001102567","doi":"10.1021/ma402008b","title":"Controlling Water Content and Proton Conductivity through Copolymer Morphology","year":2013,"lang":"en","type":"article","venue":"Macromolecules","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Copolymer; Conductivity; Polystyrene; Morphology (biology); Polymer chemistry; Proton; Materials science; Phase (matter); Neutron scattering; Scattering; Membrane; Small-angle X-ray scattering; Small-angle neutron scattering; Chemical engineering; Ionic conductivity; Analytical Chemistry (journal); Chemistry; Polymer; Composite material; Physical chemistry; Chromatography; Organic chemistry; Optics","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":[0.0000552174,0.0001553067,0.0002301754,0.00002142318,0.00005202575,0.00006741271,0.00005867835,0.0001193407,0.0005150638],"category_scores_gemma":[0.000004515209,0.000102908,0.00003177346,0.00001952844,0.00009494387,0.0001192781,0.00003656689,0.00009959074,0.0002238134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001168049,"about_ca_system_score_gemma":0.000002312557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002273163,"about_ca_topic_score_gemma":0.000001240994,"domain_scores_codex":[0.9992864,0.00003050697,0.000174283,0.0001609645,0.00005898937,0.0002888235],"domain_scores_gemma":[0.9997699,0.00001618383,0.00001611616,0.0001215654,0.0000274024,0.00004883966],"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":[0.000006744303,0.00001229627,0.0000599103,0.0001738859,0.00006058811,0.00002113957,0.0002015957,0.0002209791,0.9988415,0.00007968923,0.0001901706,0.0001315473],"study_design_scores_gemma":[0.000641391,0.00003952363,0.00006338355,0.00001729536,0.00002031962,0.00005144668,0.00005525041,0.001165083,0.9942844,0.0009687562,0.002509245,0.0001839149],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909026,0.002865005,0.000332259,0.0001861762,0.0003972301,0.00060377,0.000007066099,0.0001650217,0.004540845],"genre_scores_gemma":[0.9987975,0.0003534647,0.0003184509,0.0001252816,0.00004494646,0.0001526732,0.000009538526,0.00003233707,0.0001658076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007894873,"threshold_uncertainty_score":0.5639588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01613266264274258,"score_gpt":0.1994093456254807,"score_spread":0.1832766829827381,"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."}}