{"id":"W7060714022","doi":"","title":"Far From Home","year":2022,"lang":"en","type":"article","venue":"SOURCE Sheridan's Institutional Repository (Sheridan College)","topic":"Magnetic Field Sensors Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Student life; Human life; Government (linguistics)","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001952692,0.0004194077,0.0003938004,0.0001773504,0.001245056,0.00009014592,0.0006980126,0.0001734193,0.001632789],"category_scores_gemma":[0.00002967126,0.0005038679,0.0002236977,0.0004661499,0.0002647323,0.0002055876,0.0003049869,0.0007934609,0.00005197985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006932082,"about_ca_system_score_gemma":0.0002238894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000445229,"about_ca_topic_score_gemma":0.00002850293,"domain_scores_codex":[0.9973439,0.0001458149,0.0005880425,0.0005556633,0.0008575602,0.0005089959],"domain_scores_gemma":[0.998796,0.0001168541,0.00008789689,0.0007141992,0.00007251994,0.0002125309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006119421,0.0007535436,0.006611683,0.000331736,0.000959684,0.004158563,0.004037191,0.4732064,0.3176905,0.03577714,0.1426849,0.01317667],"study_design_scores_gemma":[0.0007479169,0.0002111986,0.003932713,0.0000342411,0.00005648924,0.0004873507,0.0007653497,0.02035512,0.01516134,0.000930166,0.9563062,0.001011885],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8567231,0.001134963,0.004814788,0.000145218,0.003258715,0.0005400355,0.0002353763,0.002221404,0.1309264],"genre_scores_gemma":[0.9869633,0.00002400995,0.003728396,0.0002733569,0.0006097779,0.0003342093,0.0000606822,0.00009576546,0.00791048],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8136213,"threshold_uncertainty_score":0.9997413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004763144475752508,"score_gpt":0.1715323132572971,"score_spread":0.1667691687815446,"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."}}