{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007200697,0.0002679533,0.0003274851,0.0003304839,0.0002481337,0.0003608842,0.0003456185,0.000341664,0.000291871],"category_scores_gemma":[0.0003146428,0.0002991281,0.0001163567,0.0004491856,0.00004443268,0.0002106643,0.0007035843,0.00181525,0.00002013956],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000333944,"about_ca_system_score_gemma":0.0003260097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009540806,"about_ca_topic_score_gemma":0.00002437354,"domain_scores_codex":[0.9976967,0.00009284196,0.0003303812,0.000492885,0.0007232687,0.0006639457],"domain_scores_gemma":[0.9986869,0.0001013205,0.00004507886,0.0005149986,0.0004984872,0.0001531983],"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":[0.000004365387,0.00001358842,0.0001001355,0.002566643,0.00003566806,0.00006186831,0.0008657365,0.9919299,0.0009073851,0.00002887418,0.00007970275,0.003406059],"study_design_scores_gemma":[0.0001317766,0.00002367837,0.00006395736,0.001325261,0.00001431085,0.00000870123,0.0009014937,0.9934643,0.002545991,0.0004210223,0.0007429513,0.000356583],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2160315,0.009617974,0.7659878,0.00007555445,0.001412938,0.0008221743,0.00007737827,0.001004809,0.004969947],"genre_scores_gemma":[0.9231881,0.002427029,0.07298412,0.00001541696,0.0004870582,0.00006177663,0.0004099374,0.0001852432,0.0002413131],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7071566,"threshold_uncertainty_score":0.9999461,"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."}}