{"id":"W2588789980","doi":"10.1063/1.4976725","title":"3D transient model to predict temperature and ablated areas during laser processing of metallic surfaces","year":2017,"lang":"en","type":"article","venue":"AIP Advances","topic":"Laser Material Processing Techniques","field":"Engineering","cited_by":4,"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; Laser; Transient (computer programming); Laser ablation; Thermal; Electromagnetic shielding; Ablation; Fabrication; Optics; Semiconductor; Titanium; Semiconductor laser theory; Optoelectronics; Composite material; Computer science; Metallurgy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001926038,0.0005266477,0.0004768099,0.0003952412,0.0003615801,0.0005897044,0.0008966198,0.001559421,0.002354218],"category_scores_gemma":[0.0007126707,0.0005107068,0.0008997935,0.0003820587,0.0004332968,0.0005616393,0.0003967813,0.0005751975,0.0005583101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009536594,"about_ca_system_score_gemma":0.0009855288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008483282,"about_ca_topic_score_gemma":0.005192848,"domain_scores_codex":[0.9998984,0.00001450295,0.000005206909,0.00001825648,0.00004480987,0.00001873684],"domain_scores_gemma":[0.9997812,0.0001074884,0.00002853218,0.00002562982,0.00004439464,0.00001286189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000229838,0.00001475888,0.0003540227,0.00002470896,0.000007538165,0.00005087061,0.00002442739,0.9908209,0.005904646,0.0007009314,0.0002092828,0.001864944],"study_design_scores_gemma":[0.000002166841,0.000005635106,0.00008533954,0.000001400948,0.000001790945,0.000009570722,0.000002708223,0.9988353,0.0007334514,0.0001284231,0.0001917395,0.000002498921],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2018758,0.0007046004,0.7747417,0.0004333839,0.0001120943,0.000182989,0.001489549,0.002610506,0.01784938],"genre_scores_gemma":[0.9555293,0.000517452,0.03345674,0.0001138813,0.00002680281,0.0004482697,0.0006534644,0.0002913031,0.008962808],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008483282,"threshold_uncertainty_score":0.01686782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008570098732517992,"score_gpt":0.2373473677090495,"score_spread":0.2287772689765315,"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."}}