{"id":"W7100031813","doi":"","title":"Which Workers Gain upon Adopting a Computer?” Canadian","year":2007,"lang":"en","type":"article","venue":"","topic":"Plant Taxonomy and Phylogenetics","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Work (physics); Public policy; Production (economics)","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":[0.002504048,0.0004080373,0.0003174386,0.001269117,0.006687036,0.005046223,0.001021404,0.002097891,0.1232826],"category_scores_gemma":[0.01345397,0.0003380038,0.000378101,0.001828698,0.003713479,0.005084459,0.002428027,0.001865119,0.02153411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01349592,"about_ca_system_score_gemma":0.01549801,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6368111,"about_ca_topic_score_gemma":0.7560969,"domain_scores_codex":[0.9977366,0.0004376298,0.00006190426,0.0003888607,0.0007587892,0.0006162439],"domain_scores_gemma":[0.994067,0.00140877,0.0002995373,0.0009245917,0.001920187,0.001379911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001557211,0.00004865482,0.009986998,0.00008684817,0.00001066448,0.0002603303,0.007591004,0.0002241561,0.0007007219,0.06806652,0.5724341,0.3404343],"study_design_scores_gemma":[0.00001205436,0.00001622782,0.007044931,0.0001129431,0.00001073707,0.0001398514,0.00744109,0.0001843897,0.0003235943,0.008062943,0.9766175,0.00003378345],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02147951,0.002487928,0.002416294,0.1063787,0.001625809,0.00005903853,0.001020714,0.0006669417,0.863865],"genre_scores_gemma":[0.2372272,0.003116879,0.005703649,0.01799325,0.0004774796,0.00007696611,0.0008064256,0.0004294954,0.7341687],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6368111,"threshold_uncertainty_score":0.7306556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02390374113863786,"score_gpt":0.1965716968339236,"score_spread":0.1726679556952858,"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."}}