{"id":"W6986115584","doi":"","title":"Olkibiosuodin maatalouden ravinnehuuhtoutumien vähentämisessä ja ravinnekierron tehostamisessa","year":2017,"lang":"fi","type":"other","venue":"Theseus (Ammattikorkeakoulujen)","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Power (physics); Work (physics); 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":[0.0005895436,0.0008057676,0.0008107446,0.0006181985,0.001795675,0.00412112,0.0006473332,0.001150325,0.03788047],"category_scores_gemma":[0.0008104476,0.0004025199,0.0007122621,0.0005290925,0.001167957,0.001963285,0.003522001,0.002275385,0.01044066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001669596,"about_ca_system_score_gemma":0.002256782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003357475,"about_ca_topic_score_gemma":0.007816429,"domain_scores_codex":[0.9992489,0.00008652826,0.00004009244,0.0002009146,0.0002716118,0.0001518195],"domain_scores_gemma":[0.9993871,0.00009887305,0.0001069543,0.00005078077,0.0001935167,0.0001626949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001480966,0.000648857,0.01398556,0.002751098,0.0001278955,0.002391551,0.005639553,0.0004206052,0.7187892,0.02125285,0.009807213,0.2227047],"study_design_scores_gemma":[0.00003665819,0.00123782,0.0271997,0.0008249608,0.0001541193,0.001552552,0.008773977,0.0005067828,0.2665709,0.005035817,0.6879918,0.0001148916],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5772653,0.03742969,0.02673388,0.006314463,0.003322173,0.000625004,0.00263369,0.001127962,0.3445478],"genre_scores_gemma":[0.5911598,0.02145983,0.02427701,0.002461032,0.0002768257,0.0004606875,0.002831411,0.0006731867,0.3564003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03788047,"threshold_uncertainty_score":0.1267228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01262889428596999,"score_gpt":0.2768121287777658,"score_spread":0.2641832344917959,"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."}}