{"id":"W4312565055","doi":"10.1002/ppj2.20056","title":"Data sharing in plant phenotyping research: Perceptions, practices, enablers, barriers and implications for science policy on data management","year":2022,"lang":"en","type":"article","venue":"The Plant Phenome Journal","topic":"Research Data Management Practices","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Canada First Research Excellence Fund","keywords":"Interoperability; Data sharing; Incentive; Reuse; Open science; Data science; Data management; Science policy; Knowledge management; Metadata; Computer science; World Wide Web; Political science; Database; Engineering","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2353516,0.0002806275,0.0006616404,0.003765995,0.008572346,0.01604369,0.002856898,0.003033588,0.002856605],"category_scores_gemma":[0.3406721,0.0007765571,0.0006479711,0.006780895,0.01579801,0.02101235,0.01648044,0.004065082,0.0003073039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009203876,"about_ca_system_score_gemma":0.02867406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01016093,"about_ca_topic_score_gemma":0.005098244,"domain_scores_codex":[0.7082156,0.2290101,0.01891191,0.008523431,0.02566757,0.00967147],"domain_scores_gemma":[0.4163012,0.4441597,0.05962216,0.0335856,0.02481797,0.0215135],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0003251911,0.0006325213,0.228707,0.001565938,0.0002462621,0.0009235793,0.4357331,0.002207541,0.002945591,0.1789052,0.007982816,0.1398253],"study_design_scores_gemma":[0.0001121804,0.0003456647,0.06521862,0.003434403,0.00009562494,0.0006686713,0.6774963,0.00466624,0.001875703,0.1388939,0.1069374,0.000255299],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8010718,0.003531052,0.02159524,0.1441542,0.0002372334,0.0004176066,0.0002742601,0.00007205648,0.02864655],"genre_scores_gemma":[0.9912313,0.0009672996,0.005094697,0.001792416,0.00005673907,0.0001865334,0.00005809568,0.00001802493,0.0005949526],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9971431,"threshold_uncertainty_score":0.9429476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5385673647772101,"score_gpt":0.4799439212227967,"score_spread":0.05862344355441346,"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."}}