{"id":"W7048263551","doi":"","title":"Kinetic parameters from statistical analysis of TREF profiles and the preparation of MgCl¦2 as supports for polymerization catalysts","year":2000,"lang":"en","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Astronomy and Astrophysical Research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Catalysis; Polymerization; Statistical analysis; Kinetic energy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001281348,0.0005888686,0.0005670433,0.001511572,0.0003789437,0.00057718,0.0007761243,0.0004940618,0.003266738],"category_scores_gemma":[0.005414329,0.0003486682,0.0006009615,0.001943811,0.0002416896,0.0006884728,0.0001769628,0.0009040487,0.001274015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001001042,"about_ca_system_score_gemma":0.0008027083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01257409,"about_ca_topic_score_gemma":0.01140274,"domain_scores_codex":[0.9992823,0.00008106027,0.00005280773,0.0001318468,0.0003795863,0.00007254134],"domain_scores_gemma":[0.9979464,0.001079883,0.0002404148,0.0001611202,0.0005242905,0.00004787189],"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":[0.001549948,0.0002726004,0.01055883,0.0007992329,0.0001160376,0.0002892599,0.0004205401,0.03916436,0.8442256,0.003905701,0.003967107,0.09473076],"study_design_scores_gemma":[0.00001175829,0.0001558212,0.02502838,0.00002020549,0.00004362859,0.0001292607,0.00008017151,0.09748507,0.8735057,0.0008203239,0.00260768,0.0001119544],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8559779,0.001159463,0.120516,0.0002040189,0.00004276443,0.0001415404,0.01264484,0.002604804,0.006708728],"genre_scores_gemma":[0.9578692,0.0008232119,0.02749598,0.00001856652,0.000007958172,0.0001354898,0.008848953,0.000668161,0.004132564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01257409,"threshold_uncertainty_score":0.02500182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002267530004067683,"score_gpt":0.1836590975813508,"score_spread":0.1813915675772831,"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."}}