{"id":"W2008573197","doi":"10.1111/j.1744-7402.2006.02075.x","title":"Processing and Characterization of Oxygen Sensors Prepared From Freeze‐Dried Calcia‐Stabilized Zirconia Powders","year":2006,"lang":"en","type":"article","venue":"International Journal of Applied Ceramic Technology","topic":"Advancements in Solid Oxide Fuel Cells","field":"Materials Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Materials science; Microstructure; Calcination; Cubic zirconia; Scanning electron microscope; Oxygen sensor; Chemical engineering; Oxygen; Electrolyte; Sintering; Characterization (materials science); Fast ion conductor; Texture (cosmology); Pressing; Phase (matter); Metallurgy; Composite material; Nanotechnology; Electrode; Ceramic; Catalysis; Physical chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002331478,0.0002659657,0.0003879202,0.000265794,0.000131221,0.0002210386,0.0003131441,0.0001988345,0.0006648495],"category_scores_gemma":[0.0003076621,0.0001865654,0.0001944713,0.0001944798,0.000185372,0.0001680221,0.0001031939,0.0002580399,0.0001870941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002159095,"about_ca_system_score_gemma":0.0001829488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007431715,"about_ca_topic_score_gemma":0.001121924,"domain_scores_codex":[0.9998951,0.000005147152,0.000008353602,0.00002791034,0.00004918148,0.0000142825],"domain_scores_gemma":[0.9998908,0.00002656789,0.0000250177,0.00001236079,0.00003411199,0.00001114724],"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":[0.00002576773,0.000006427375,0.00007062542,0.00002327527,0.000001971877,0.000015384,0.000009214784,0.00003883126,0.9989643,0.0000261327,0.00001302492,0.0008050203],"study_design_scores_gemma":[0.000008088267,0.00005724258,0.001255633,0.000002200136,0.000007512689,0.00004392341,0.000006847437,0.0003725553,0.9976032,0.00001226909,0.0006284089,0.000002141396],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9704188,0.001457464,0.02565241,0.00005183652,0.00005683195,0.0001508524,0.0007512235,0.0001741195,0.001286532],"genre_scores_gemma":[0.9603035,0.001420599,0.03422101,0.00005532647,0.00001791898,0.0001229851,0.00142079,0.0000726486,0.002365222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007431715,"threshold_uncertainty_score":0.002224207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005245512648225219,"score_gpt":0.2399934808141118,"score_spread":0.2347479681658866,"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."}}