{"id":"W4236433044","doi":"10.17504/protocols.io.4g2gtye","title":"Measuring chlorophylls and carotenoids in plant tissue v1","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Water Quality Monitoring and Analysis","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Carotenoid; Measure (data warehouse); Observatory; Chlorophyll; Environmental science; Biology; Botany; Remote sensing; Geography; Computer science; Physics; Astronomy; Data mining","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":[0.0006844127,0.001891238,0.001058959,0.00128914,0.001798673,0.00114789,0.001631407,0.0009170994,0.0105423],"category_scores_gemma":[0.0005892147,0.000892998,0.0009616851,0.001823517,0.0008119761,0.0009258594,0.001404288,0.003488841,0.01037912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001637982,"about_ca_system_score_gemma":0.002267197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02033352,"about_ca_topic_score_gemma":0.03657215,"domain_scores_codex":[0.9985431,0.00009345048,0.00008282121,0.0006055188,0.0004723911,0.0002026734],"domain_scores_gemma":[0.99926,0.0001048324,0.00006434476,0.0002150989,0.0002534506,0.0001022457],"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":[0.00006536924,0.00001751229,0.0001684984,0.0001104853,0.000007098102,0.00003220201,0.00006037399,0.00004049813,0.9954721,0.000232269,0.0005580804,0.003235627],"study_design_scores_gemma":[0.00003794978,0.0003715135,0.01688403,0.00007059773,0.00007391548,0.0002855537,0.0001172318,0.0008606755,0.907769,0.0007122798,0.07275178,0.00006548235],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2719571,0.008455058,0.5687876,0.0003785523,0.001082795,0.009634042,0.05734542,0.01212114,0.07023837],"genre_scores_gemma":[0.1982712,0.007091358,0.4381966,0.001395784,0.0001626968,0.01491395,0.1687909,0.007218576,0.163959],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02033352,"threshold_uncertainty_score":0.04043037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03739933496532766,"score_gpt":0.2410261267210873,"score_spread":0.2036267917557596,"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."}}