{"id":"W7048246412","doi":"","title":"+91-9116799099 job problem solution in vancouver","year":2021,"lang":"en","type":"other","venue":"OSF Preprints (OSF Preprints)","topic":"Magnetic Field Sensors Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bengali; MAGIC (telescope); Cheating; Phone; Kali","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":["insufficient_payload"],"category_scores_codex":[0.0007047756,0.0007319403,0.0003806888,0.000745611,0.006132542,0.004109416,0.001157126,0.001422645,0.4547923],"category_scores_gemma":[0.001842728,0.0003412314,0.000321333,0.001270385,0.0004575645,0.0007893709,0.0025419,0.001346177,0.2069753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005685365,"about_ca_system_score_gemma":0.01600521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3127272,"about_ca_topic_score_gemma":0.6994343,"domain_scores_codex":[0.9992715,0.0000813443,0.00002198816,0.0000999765,0.0002885113,0.0002367318],"domain_scores_gemma":[0.997048,0.00009475485,0.00002334562,0.00005855151,0.0009785416,0.001796866],"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":[0.00005873418,0.0002341418,0.00150854,0.0001085626,0.000005255259,0.0001966063,0.0002903298,0.0004408029,0.0003802266,0.001291118,0.8899592,0.1055265],"study_design_scores_gemma":[0.00002523559,0.00006562628,0.003602071,0.00008676402,0.000002686488,0.00005061185,0.002695466,0.0008670865,0.000226656,0.0006040794,0.9917623,0.0000115051],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01445435,0.0009182438,0.001379209,0.01036094,0.001782833,0.0004486836,0.002892324,0.0009293842,0.9668341],"genre_scores_gemma":[0.01143595,0.0005661037,0.001112123,0.0004404607,0.00004993528,0.00005663255,0.00164089,0.000180476,0.9845175],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5452077,"threshold_uncertainty_score":0.7776726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008506336841574026,"score_gpt":0.2216749850452661,"score_spread":0.2131686482036921,"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."}}