{"id":"W6920418124","doi":"10.6068/dp14ba7b938c781","title":"Trend 2008 - 2012. Statistics Canada. CANSIM: Agriculture - Farm Financial Statistics | Country: Canada | Table: Specialized greenhouse producers' operating expenses | Variable: Electricity, Specialized greenhouse flower and plant | Units: $CAD, 2008-2012. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-003.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Economic statistics; Agriculture; Greenhouse; Descriptive statistics; Revenue; Summary statistics; Census; 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":[0.002272391,0.002401244,0.0024825,0.009634566,0.003138296,0.005150006,0.004937505,0.001484378,0.1068224],"category_scores_gemma":[0.01839333,0.001873913,0.002061409,0.04285831,0.0006209873,0.002727324,0.002322314,0.002773469,0.06363621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06179336,"about_ca_system_score_gemma":0.1529091,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9945073,"about_ca_topic_score_gemma":0.9923725,"domain_scores_codex":[0.995209,0.0002702695,0.0004538195,0.0005433332,0.002414027,0.001109578],"domain_scores_gemma":[0.9604783,0.001260588,0.001119887,0.00106423,0.034336,0.001741006],"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":[0.00001966011,0.000005202724,0.0007206203,0.0002107271,0.00001573711,0.000006263658,0.00001762721,0.00009722856,0.00001011696,0.0003993543,0.9967981,0.001699448],"study_design_scores_gemma":[0.0000954881,0.000009012117,0.01703772,0.0006764065,0.00004859658,0.00002093626,0.0003391897,0.0003964297,0.0001631016,0.0005598697,0.9805824,0.00007076488],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005060136,0.00005666619,0.00002959782,0.0001577072,0.00003268796,0.00001618009,0.9981173,0.00007615604,0.001462998],"genre_scores_gemma":[0.0009672656,0.0003783875,0.0005665797,0.0002175555,0.00002204923,0.0001374897,0.9904834,0.0001666471,0.00706069],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1068224,"threshold_uncertainty_score":0.4483443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02212795774061234,"score_gpt":0.2381422713561707,"score_spread":0.2160143136155583,"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."}}