{"id":"W2407905567","doi":"","title":"ANISOTROPY OPTIMIZATION OF GIANT MAGNETOIMPEDANCE SENSORS","year":2004,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Magnetic Properties and Applications","field":"Materials Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Anisotropy; Magnetostriction; Materials science; Giant magnetoimpedance; Amplitude; Condensed matter physics; Magnetic field; Magnetic anisotropy; Transverse plane; Magnetization; Nuclear magnetic resonance; Stress (linguistics); Composite material; Magnetoresistance; Optics; Giant magnetoresistance; Physics; Structural engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002961215,0.0002031351,0.0002605319,0.0001235652,0.0001698919,0.00007515098,0.0004179654,0.0001321591,0.0003914828],"category_scores_gemma":[0.00009038566,0.000186859,0.00008606248,0.0003357921,0.0001579185,0.000194961,0.0001277269,0.0001221626,0.0000445071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001726118,"about_ca_system_score_gemma":0.0001752483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005820485,"about_ca_topic_score_gemma":0.0002576264,"domain_scores_codex":[0.9984256,0.00004958602,0.0004574661,0.0003458812,0.0002848219,0.0004366556],"domain_scores_gemma":[0.998771,0.00002779668,0.000232746,0.0006780372,0.0001335338,0.000156963],"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":[0.00003917701,0.0001429684,0.0001430122,0.00003028307,0.000003817651,0.000005641161,0.0001332465,0.2942432,0.6615487,0.04182548,0.0002098285,0.001674544],"study_design_scores_gemma":[0.000931893,0.0003959233,0.004613438,0.00008300741,0.00004037784,0.00008860861,0.0001800379,0.1598319,0.8272775,0.004658854,0.00139487,0.0005035366],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3362799,0.0005466802,0.6592113,0.002444309,0.00006199889,0.0004776852,0.00004731233,0.0002943782,0.0006365299],"genre_scores_gemma":[0.6387029,0.0001917053,0.3600643,0.0003808805,0.00004854257,0.0001874951,0.000008997265,0.00002864362,0.0003864641],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3024231,"threshold_uncertainty_score":0.8798872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008799713181923154,"score_gpt":0.2153854834161182,"score_spread":0.2065857702341951,"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."}}