{"id":"W7058126676","doi":"","title":"MICROSOFT DEEPENS INVESTMENT IN CANADA WITH THE OPENING OF NEW HEADQUARTERS AND EXPANSION OF OPERATIONS TO EMPOWER ECONOMIC GROWTH","year":2022,"lang":"en","type":"other","venue":"","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Investment (military); Government (linguistics); Work (physics); Order (exchange)","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":[],"consensus_categories":[],"category_scores_codex":[0.0009328809,0.000853804,0.0003178756,0.001778023,0.005850853,0.006415877,0.0009452344,0.003479889,0.1145265],"category_scores_gemma":[0.003361249,0.0003836211,0.0005538896,0.001482737,0.001710132,0.001791712,0.002161219,0.002951315,0.02100475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03554239,"about_ca_system_score_gemma":0.1232899,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9496375,"about_ca_topic_score_gemma":0.9803525,"domain_scores_codex":[0.9980314,0.00003467699,0.00001602343,0.00007819037,0.001153769,0.0006858652],"domain_scores_gemma":[0.9949162,0.0001567314,0.0000639747,0.0001090474,0.00216014,0.002593987],"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":[0.00006332366,0.00004693829,0.001424751,0.00003367716,0.000004988544,0.0001055645,0.0001229938,0.0002947455,0.0005872538,0.03235485,0.9297774,0.03518345],"study_design_scores_gemma":[0.00002225381,0.000024438,0.004017318,0.0000467201,0.000005765034,0.00004074253,0.0004094192,0.0008158223,0.0009084809,0.003237707,0.9904466,0.00002470493],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01202203,0.000910209,0.001298211,0.03559447,0.001866307,0.0001495213,0.006263816,0.001607926,0.9402875],"genre_scores_gemma":[0.02116663,0.000582087,0.0008190975,0.002775966,0.0001143484,0.0000182485,0.001217393,0.000259873,0.9730463],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1145265,"threshold_uncertainty_score":0.3831294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006269510222977725,"score_gpt":0.2196979121905639,"score_spread":0.2134284019675862,"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."}}