{"id":"W2138778258","doi":"10.1109/ccece.2004.1347571","title":"Flux guiding in an aluminum honeycomb lattice observed through magnetic resonance imaging","year":2004,"lang":"en","type":"article","venue":"","topic":"Metamaterials and Metasurfaces Applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation","keywords":"Materials science; Electromagnetic coil; Attenuation; Magnetic flux; Magnetic field; Lattice (music); Aluminium; Flux (metallurgy); Honeycomb structure; Nuclear magnetic resonance; Permeability (electromagnetism); Honeycomb; Condensed matter physics; Composite material; Acoustics; Optics; Physics; Engineering; Metallurgy; Electrical engineering; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007762337,0.0001824197,0.0002745935,0.00004051581,0.0001589265,0.0001978338,0.0004363249,0.00004793564,0.001813097],"category_scores_gemma":[0.00006284573,0.0001632921,0.00003752766,0.0002812592,0.00008237487,0.0006891005,0.0001054623,0.00005027295,0.0005970362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006517896,"about_ca_system_score_gemma":0.00006184493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001070154,"about_ca_topic_score_gemma":0.0003493958,"domain_scores_codex":[0.9982217,0.0001092855,0.000483367,0.0005055408,0.0002366135,0.0004434781],"domain_scores_gemma":[0.9990857,0.00004256327,0.00009410363,0.0006164278,0.00006875457,0.00009241537],"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":[0.000009650183,0.00008202878,0.0005781177,0.00001175371,4.088485e-7,0.000006792075,0.0003937566,0.0001366357,0.9848719,0.01310168,0.0001451462,0.0006621329],"study_design_scores_gemma":[0.0009442008,0.00004906682,0.01353829,0.00005439874,0.00001693443,0.00001161892,0.0003403363,0.0002315587,0.9564983,0.009166754,0.01881971,0.00032881],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926393,0.001825997,0.000959875,0.0008534677,0.0003579386,0.0003320369,0.00001594637,0.0001433305,0.002872101],"genre_scores_gemma":[0.8933966,0.00005679992,0.105048,0.0006028753,0.00007688639,0.00008188786,0.00001466152,0.00002747296,0.00069482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1040881,"threshold_uncertainty_score":0.9990994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07752076076655166,"score_gpt":0.2933325005120452,"score_spread":0.2158117397454935,"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."}}