{"id":"W4289516851","doi":"10.20944/preprints202208.0075.v1","title":"Waste Plastic Direct Extrusion Hangprinter","year":2022,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Additive Manufacturing and 3D Printing Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Compounding; Limiting; Extrusion; Dram; Plastic waste; Fused filament fabrication; Process (computing); Process engineering; Materials science; Computer science; Waste management; Mechanical engineering; Engineering; 3D printing; Composite material; Computer hardware","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","open_science","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004487878,0.0006690492,0.0006338093,0.0004152652,0.0002016595,0.00004545106,0.00143208,0.000448337,0.005434042],"category_scores_gemma":[0.0004847724,0.0007278215,0.0003327523,0.0001615519,0.0001261,0.00007480637,0.008277579,0.002517097,0.001395415],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003903693,"about_ca_system_score_gemma":0.00004077512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005017678,"about_ca_topic_score_gemma":0.000007390708,"domain_scores_codex":[0.9971714,0.0001033028,0.0005566872,0.001099574,0.000433871,0.0006351785],"domain_scores_gemma":[0.9975176,0.0002596551,0.0001719836,0.001889621,0.00004778432,0.0001133184],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001784002,0.0004515621,0.2503776,0.003964368,0.002116661,0.0005165284,0.003485372,0.668882,0.0306046,0.0008774328,0.007061136,0.03148435],"study_design_scores_gemma":[0.0006068252,0.00005108543,0.1739431,0.0008805077,0.0002013739,0.00002425752,0.0006529712,0.01064923,0.6948006,0.00427902,0.1112813,0.00262971],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9366162,0.0002422506,0.0008960866,0.00007904959,0.003532584,0.000435578,0.00009273367,0.00526147,0.05284405],"genre_scores_gemma":[0.9961312,0.000309272,0.0003519655,0.00002194315,0.0002609509,0.000450209,0.00008951503,0.000166614,0.002218264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.664196,"threshold_uncertainty_score":0.9997841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07302073166972649,"score_gpt":0.2893143978706447,"score_spread":0.2162936662009182,"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."}}