{"id":"W7070628946","doi":"","title":"Polyolefin Nanocomposites with Improved Performance","year":2005,"lang":"en","type":"article","venue":"NPARC","topic":"QR Code Applications and Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Polyolefin; Nanocomposite; Composite number; Compounding; Polyethylene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004028964,0.00006838708,0.00005958695,0.00004785527,0.00009419806,0.00006149963,0.0005936484,0.00002914034,0.00001487706],"category_scores_gemma":[0.000001840758,0.00005034323,0.00001341924,0.0002271953,0.0000405985,0.0002649884,0.0001214732,0.00006757826,0.00008054291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001638143,"about_ca_system_score_gemma":0.00001977773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002484725,"about_ca_topic_score_gemma":0.000004737533,"domain_scores_codex":[0.9995064,0.000003452735,0.00007271134,0.0001838316,0.00007837027,0.0001551975],"domain_scores_gemma":[0.9994307,0.00001240793,0.00002893601,0.0004746475,0.00002921302,0.00002405096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000003319364,0.00004614501,0.001272029,0.000003763321,0.000006381784,5.857852e-7,0.00007021643,0.00002161447,0.2087031,0.101174,0.0005060426,0.6881928],"study_design_scores_gemma":[0.0004654638,0.0002600986,0.009308369,0.00001735745,0.000004794564,0.00004686773,0.00001624311,0.2019938,0.7179828,0.00322608,0.06634747,0.0003306553],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7439143,0.0000799187,0.2172435,0.008658435,0.00002113011,0.0001743686,8.412447e-7,0.0008504645,0.02905708],"genre_scores_gemma":[0.7047468,0.00001253747,0.2948247,0.0001431496,0.00001376917,0.00003338447,3.292837e-7,0.000002916107,0.0002222875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6878622,"threshold_uncertainty_score":0.2052938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006355921994219319,"score_gpt":0.197251448459163,"score_spread":0.1908955264649437,"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."}}