{"id":"W7062287284","doi":"","title":"Top 50 in agriculture winner on tech and mental health AND how Statistics Canada gathers and compiles agriculture information","year":2021,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Adaptive optics and wavefront sensing","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Work (physics); Quarter (Canadian coin); Land grant; Mental health; High tech","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.004509765,0.0005944346,0.0005988962,0.0031674,0.01391387,0.01096539,0.001709355,0.002940851,0.07485777],"category_scores_gemma":[0.01809043,0.0008572878,0.000609341,0.005854563,0.003184269,0.00471008,0.004815174,0.004395595,0.02070349],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03534809,"about_ca_system_score_gemma":0.1223825,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9595134,"about_ca_topic_score_gemma":0.985435,"domain_scores_codex":[0.9900327,0.0008711958,0.0002687671,0.0004215934,0.005042727,0.003363091],"domain_scores_gemma":[0.9697869,0.002555534,0.0006173143,0.0006593172,0.01302736,0.0133536],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000249676,0.00000417895,0.000613327,0.00001625185,0.00000129666,0.00001060859,0.0001909872,0.000004327728,0.00001238679,0.0007185333,0.9903499,0.008075698],"study_design_scores_gemma":[0.000006280787,0.000006124776,0.01247327,0.0001835646,0.000006216352,0.00003596011,0.004169006,0.00002782699,0.00006077695,0.0003944782,0.9825978,0.00003857155],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.004576611,0.009756893,0.0005522594,0.5741329,0.0140082,0.0002528343,0.01173647,0.0008180958,0.3841658],"genre_scores_gemma":[0.051143,0.01811913,0.00135741,0.1951494,0.002738185,0.0003046093,0.009205892,0.001089557,0.7208928],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9954903,"threshold_uncertainty_score":0.2564695,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00330009432889661,"score_gpt":0.1680431006637609,"score_spread":0.1647430063348643,"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."}}