{"id":"W3135584128","doi":"10.1016/j.coco.2021.100697","title":"High strength particulate aluminum matrix composite design: Synergistic strengthening strategy","year":2021,"lang":"en","type":"article","venue":"Composites Communications","topic":"Aluminum Alloys Composites Properties","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures","keywords":"Materials science; Composite number; Composite material; Aluminium; Strain hardening exponent; Strengthening mechanisms of materials; Matrix (chemical analysis); Compressive strength; Particulates; Ultimate tensile strength","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001966526,0.0004776513,0.0005253681,0.0001546188,0.0006080603,0.0003738071,0.001465862,0.0001562574,0.0001535683],"category_scores_gemma":[0.00005198506,0.0005266231,0.0001668999,0.0006363498,0.0002919422,0.000354073,0.0006985192,0.000615986,0.000284925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001849448,"about_ca_system_score_gemma":0.00009128886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005364896,"about_ca_topic_score_gemma":0.00007259141,"domain_scores_codex":[0.9974414,0.0004217345,0.0007922024,0.0004026246,0.0003170047,0.0006250134],"domain_scores_gemma":[0.9956247,0.0008621408,0.0001171336,0.002865231,0.0002906737,0.0002401763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002404893,0.000369821,0.0008998523,0.0001138235,0.0005841226,0.00007069891,0.0005937825,0.4806269,0.4998961,0.01047883,0.002371186,0.003970746],"study_design_scores_gemma":[0.001060657,0.0001245062,0.002105183,0.0003360927,0.0004129726,0.0001448933,0.0003075806,0.7025611,0.2829269,0.001412593,0.007201595,0.001405976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8436419,0.03909251,0.1008345,0.001364505,0.0008960956,0.000965312,0.0001700131,0.003833868,0.009201213],"genre_scores_gemma":[0.8890986,0.0007777677,0.1088583,0.00005163127,0.00007500744,0.0001040849,0.0004340734,0.0001150708,0.0004854851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2219341,"threshold_uncertainty_score":0.9997185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03457490532246139,"score_gpt":0.2557835846882857,"score_spread":0.2212086793658243,"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."}}