{"id":"W4220985046","doi":"10.1038/s41467-022-28694-x","title":"Keyhole fluctuation and pore formation mechanisms during laser powder bed fusion additive manufacturing","year":2022,"lang":"en","type":"article","venue":"Nature Communications","topic":"Additive Manufacturing Materials and Processes","field":"Engineering","cited_by":385,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Argonne National Laboratory; Engineering and Physical Sciences Research Council; Office of Science; Office of Naval Research; Research Councils UK; Office of Naval Research Global; Royal Academy of Engineering; Alan Turing Institute; U.S. Department of Energy; U.S. Department of Defense","keywords":"Keyhole; Porosity; Bubble; Materials science; Liquid bubble; Shrinkage; Fusion; Chemical physics; Mechanics; Composite material; Chemistry; Welding; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001394562,0.0001479735,0.0001225974,0.0001257562,0.0008371133,0.0000618194,0.000331592,0.00009912984,0.000308105],"category_scores_gemma":[0.00002562652,0.0001580255,0.00002992743,0.0001015688,0.00002864813,0.0003219796,0.0004302063,0.0005799661,0.00000805657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001062507,"about_ca_system_score_gemma":0.000008607506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004790939,"about_ca_topic_score_gemma":0.00002944829,"domain_scores_codex":[0.9992575,0.00007862299,0.0001880841,0.0001384955,0.0001751528,0.0001621542],"domain_scores_gemma":[0.9992851,0.0000929192,0.00006872721,0.0004673592,0.00004232805,0.00004356509],"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":[0.0004344356,0.0007133445,0.0001666086,0.001975406,0.0007815414,0.00006214002,0.02713147,0.04704827,0.7325171,0.04152472,0.03520999,0.112435],"study_design_scores_gemma":[0.0005397913,0.00003732005,0.006059892,0.00003890942,0.00004077556,0.00006116352,0.001070168,0.00338584,0.9357334,0.005171014,0.0474395,0.0004222695],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991241,0.001560781,0.001615902,0.0007482873,0.0004211138,0.0004636615,0.0005826483,0.0005751923,0.002791386],"genre_scores_gemma":[0.9962252,0.0004752263,0.001635035,0.0001038955,0.00004138729,0.0001631829,0.001256668,0.00003260124,0.00006676068],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2032163,"threshold_uncertainty_score":0.6444095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008550099230522473,"score_gpt":0.2212789618958229,"score_spread":0.2127288626653004,"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."}}