{"id":"W3200386066","doi":"10.21203/rs.3.rs-893942/v1","title":"Thin Floor Milling Using Moving Support","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Advanced machining processes and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Association of Emergency Physicians","funders":"","keywords":"Rigidity (electromagnetism); Machining; Surface (topology); Materials science; Milling cutter; Mechanical engineering; Computer science; Structural engineering; Engineering; Composite material; Geometry; Mathematics","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":[0.000148375,0.0003791799,0.0003755381,0.0002796681,0.0001843799,0.0003500624,0.0003851844,0.0003317148,0.001255883],"category_scores_gemma":[0.0002548438,0.0002344973,0.0002449824,0.0002235229,0.0003324626,0.0002527512,0.0004089614,0.0004237866,0.0002468897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001327907,"about_ca_system_score_gemma":0.0002840033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000412113,"about_ca_topic_score_gemma":0.0007272772,"domain_scores_codex":[0.9998341,0.00001138301,0.000008070716,0.00003473339,0.00008994442,0.00002168562],"domain_scores_gemma":[0.999764,0.00004875425,0.0000582659,0.00005912659,0.00004423143,0.0000255613],"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":[0.000222259,0.0000469337,0.0008587023,0.0002294188,0.00002258899,0.0002981398,0.00006984857,0.02583841,0.8987641,0.001749979,0.0003607359,0.07153887],"study_design_scores_gemma":[0.00009237665,0.001248877,0.006347822,0.00003697852,0.00004594526,0.0007225341,0.00009629408,0.355597,0.6277747,0.001701446,0.006273826,0.00006226303],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5526456,0.0003943999,0.4409198,0.00005460288,0.00006596963,0.00006060403,0.00006701099,0.0006556272,0.005136349],"genre_scores_gemma":[0.851953,0.00008565263,0.1462959,0.00001662182,0.00000783732,0.00001798321,0.00004745279,0.00002857862,0.001546993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001255883,"threshold_uncertainty_score":0.004201293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06792497347245491,"score_gpt":0.3843127827588114,"score_spread":0.3163878092863565,"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."}}