{"id":"W7002001338","doi":"","title":"Mittausdatan käyttö kaukolämmitteisten asuinrakennusten lämpimän käyttövesisiirtimen mitoituksen optimoinnissa","year":2019,"lang":"fi","type":"other","venue":"Theseus (Ammattikorkeakoulujen)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Life style; Paid work; Quarter (Canadian coin)","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":[0.002214109,0.0013986,0.0009695565,0.0009443369,0.002032778,0.007839965,0.001216493,0.001489397,0.06761382],"category_scores_gemma":[0.005724099,0.0005769847,0.0008105541,0.0009652426,0.001179468,0.0046217,0.003458976,0.00267315,0.02418539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002404114,"about_ca_system_score_gemma":0.004858236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006030112,"about_ca_topic_score_gemma":0.01277841,"domain_scores_codex":[0.9976713,0.0004310776,0.0001249824,0.0004308932,0.001025751,0.0003159388],"domain_scores_gemma":[0.9966935,0.0007873796,0.0002980112,0.0003938947,0.001325051,0.0005022571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00165217,0.000848341,0.01765101,0.002038531,0.000214073,0.001087456,0.008007022,0.008759324,0.05302956,0.104416,0.1088437,0.6934528],"study_design_scores_gemma":[0.00007680606,0.000634415,0.01411537,0.0006165158,0.0001477649,0.0008499463,0.007144618,0.01336682,0.02388677,0.03494405,0.9039841,0.000232792],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.122622,0.01391792,0.1393959,0.01714348,0.003441988,0.0005691331,0.002117791,0.004252429,0.6965393],"genre_scores_gemma":[0.4144219,0.008788562,0.09207317,0.002307492,0.0008128624,0.0004392414,0.003162541,0.001825877,0.4761684],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06761382,"threshold_uncertainty_score":0.2261907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02128046223667181,"score_gpt":0.2599690430230083,"score_spread":0.2386885807863365,"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."}}