{"id":"W7058385515","doi":"","title":"In Montreal, Obama defends his legacy as Trump aims to dismantle it in Washington","year":2017,"lang":"en","type":"other","venue":"","topic":"Particle accelerators and beam dynamics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government (linguistics); State (computer science); Presidential system; Agency (philosophy); Politics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001679767,0.000706021,0.0004376968,0.001390527,0.01439186,0.008907539,0.001369428,0.008168899,0.1590661],"category_scores_gemma":[0.004396494,0.0004817213,0.0005519655,0.001011506,0.00242713,0.003331497,0.003277382,0.00796897,0.03726492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01048112,"about_ca_system_score_gemma":0.01610478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3036129,"about_ca_topic_score_gemma":0.6502837,"domain_scores_codex":[0.998602,0.00007667243,0.00002202911,0.0001404271,0.0006026097,0.0005563749],"domain_scores_gemma":[0.9982771,0.0001998315,0.00004503562,0.0001390027,0.0005859046,0.000753323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002728838,0.00002834004,0.0007803955,0.00002069124,0.000004000967,0.0001836635,0.0002858749,0.00006412698,0.000131428,0.06559547,0.9121588,0.02071998],"study_design_scores_gemma":[0.000002496477,0.000004320298,0.0003406765,0.0000194938,0.000001228506,0.00001952059,0.0001909794,0.00002455785,0.00009017985,0.001126387,0.9981754,0.000004748771],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.003239514,0.001457112,0.0006512674,0.05322089,0.005560339,0.00005850333,0.0006357371,0.0005010432,0.9346756],"genre_scores_gemma":[0.008021367,0.0003643873,0.0001655443,0.004332331,0.0002589809,0.00001229458,0.000126127,0.0001505052,0.9865685],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.8409339,"threshold_uncertainty_score":0.6036914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01181674052148036,"score_gpt":0.2494883869491087,"score_spread":0.2376716464276283,"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."}}