{"id":"W6958052491","doi":"10.6068/dp14ba8b84bc839","title":"Trend 2002 - 2009. Statistics Canada. CANSIM: Education, Training and Learning - Fields of Study | Country: Canada | Table: College enrolments, by registration status, program level, Classification of Instructional Programs, Primary Grouping (CIP_PG) and sex | Variable: Mathematics, computer and information sciences, College post-diploma program, Females, Part-time student | Units: #, 2002-2009. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-071.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Statistics education; Census; Economic statistics; Statistical analysis; Publication; Socioeconomic status; Official statistics","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":[0.002697529,0.002521689,0.003014103,0.01008204,0.003383865,0.004982116,0.005381984,0.001593257,0.08815666],"category_scores_gemma":[0.0242555,0.001803423,0.002239362,0.0475759,0.0006848935,0.002418903,0.002404742,0.003168463,0.04930749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06034176,"about_ca_system_score_gemma":0.1666564,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9941637,"about_ca_topic_score_gemma":0.9918944,"domain_scores_codex":[0.9941796,0.0003756996,0.0007368542,0.0007472484,0.002742996,0.001217673],"domain_scores_gemma":[0.9481845,0.001936521,0.001551165,0.001429597,0.04462611,0.002272129],"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":[0.00002850712,0.000006670487,0.001092843,0.0003118931,0.00002388324,0.000006076356,0.00002215636,0.0001189772,0.00001107282,0.0003569385,0.9964153,0.001605684],"study_design_scores_gemma":[0.0001786064,0.00001332964,0.02594673,0.0009945802,0.00008304542,0.0000253324,0.0004564085,0.0004350385,0.0001718519,0.0006544374,0.9709514,0.00008934164],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004498295,0.00004172354,0.00002153408,0.0001115685,0.00002701572,0.00001524811,0.9989962,0.00005053192,0.0006911708],"genre_scores_gemma":[0.0008510305,0.0002781083,0.0004449405,0.000182994,0.00002015654,0.0001528029,0.9943174,0.0001071026,0.003645444],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08815666,"threshold_uncertainty_score":0.4378121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04754096861746865,"score_gpt":0.27399789471592,"score_spread":0.2264569260984514,"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."}}