{"id":"W2606173436","doi":"10.1016/j.jpowsour.2017.03.100","title":"Thermal conductivity of catalyst layer of polymer electrolyte membrane fuel cells: Part 2 – Analytical modeling","year":2017,"lang":"en","type":"article","venue":"Journal of Power Sources","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Automotive Fuel Cell Cooperation (Canada); Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Electrolyte; Proton exchange membrane fuel cell; Membrane; Polymer; Thermal conductivity; Materials science; Chemical engineering; Fuel cells; Catalysis; Conductivity; Layer (electronics); Composite material; Chemistry; Organic chemistry; Electrode; Engineering; Physical 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":[],"consensus_categories":[],"category_scores_codex":[0.0004059967,0.0001440923,0.0005046309,0.00009993037,0.00005209273,0.00004187072,0.0003103991,0.0001298696,0.000197647],"category_scores_gemma":[0.00002528718,0.000105667,0.0002038041,0.00003864073,0.00009618201,0.0002354279,0.00003730129,0.0002323342,0.000004012594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001357116,"about_ca_system_score_gemma":0.00002859573,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003558914,"about_ca_topic_score_gemma":0.000002124493,"domain_scores_codex":[0.9988472,0.00003073338,0.0005768294,0.00008285217,0.0002567484,0.0002056185],"domain_scores_gemma":[0.9990783,0.00003299708,0.0004242166,0.0002667104,0.0001110133,0.00008680558],"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":[0.00008423982,0.0000600321,0.0001215884,0.0002661046,0.0003842122,0.0000185355,0.0005245713,0.08422391,0.9141569,0.00002040052,0.00009452562,0.00004502456],"study_design_scores_gemma":[0.0005774882,0.0001193996,0.00008526901,0.0001171893,0.0001810788,0.00002540253,0.0001187359,0.02348431,0.9745249,0.00003412576,0.0005823529,0.0001498159],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898947,0.004372025,0.0001059663,0.00005254582,0.0006977795,0.00003482015,0.000009935756,0.0000102105,0.004821966],"genre_scores_gemma":[0.9990646,0.0005531013,0.00006208538,0.000005768713,0.0001738224,2.886311e-7,5.102642e-7,0.00002485796,0.0001150209],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06073961,"threshold_uncertainty_score":0.4308977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0176349348748567,"score_gpt":0.2309796346012001,"score_spread":0.2133446997263434,"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."}}