{"id":"W7076049585","doi":"10.2139/ssrn.5394736","title":"In Pursuit of Achieving High-Speed Drilling of 3d-Printed Inconel-718 Under Extreme Condition","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Drilling; Drill; Machining; Enhanced Data Rates for GSM Evolution; Thrust; Cutting tool; Tool wear; Machinability; Inconel","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000235296,0.0002383028,0.0002327443,0.0002222046,0.0003330161,0.000540828,0.0003879204,0.0006384474,0.001677227],"category_scores_gemma":[0.0005589147,0.0001587299,0.0001723101,0.0003279437,0.000371022,0.000571539,0.0005074443,0.000483395,0.000555266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001636887,"about_ca_system_score_gemma":0.0003568917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005358753,"about_ca_topic_score_gemma":0.001644425,"domain_scores_codex":[0.9997612,0.00001675926,0.00001372005,0.00004232883,0.0001340662,0.00003193518],"domain_scores_gemma":[0.9997787,0.00004656968,0.00004537585,0.00007069101,0.00004611003,0.00001247078],"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":[0.0002478252,0.00004125,0.002304912,0.0003094202,0.00001173169,0.0007306534,0.0003657569,0.01606681,0.9150658,0.004997724,0.0009402139,0.05891779],"study_design_scores_gemma":[0.0000286985,0.0006710628,0.005585466,0.00002575145,0.00001717928,0.001192611,0.0003113352,0.04055887,0.9300451,0.002266876,0.01926354,0.00003356656],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.847067,0.0004357066,0.1343014,0.0004453436,0.0001419636,0.00004473722,0.0002146723,0.0009319748,0.01641706],"genre_scores_gemma":[0.9355264,0.0001310963,0.0609123,0.00003326832,0.000008262893,0.00001715151,0.000098791,0.00002185159,0.003250752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001677227,"threshold_uncertainty_score":0.005610824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01758215199674367,"score_gpt":0.2530544816028396,"score_spread":0.2354723296060959,"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."}}