{"id":"W4400200459","doi":"10.1037/0000409-035","title":"How to build up big team science: A practical guide for large-scale collaborations.","year":2024,"lang":"en","type":"book-chapter","venue":"American Psychological Association eBooks","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Manitoba; Concordia University","funders":"Social Sciences and Humanities Research Council of Canada; John Templeton Foundation","keywords":"Scale (ratio); Big data; Data science; Computer science; Geography; Cartography; Data mining","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"],"consensus_categories":[],"category_scores_codex":[0.01947923,0.003131699,0.001185168,0.004077497,0.00428306,0.01143999,0.005427682,0.006056795,0.04650726],"category_scores_gemma":[0.0308413,0.00263632,0.001283792,0.00389397,0.007555825,0.01623318,0.008861705,0.01118696,0.05397898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003061393,"about_ca_system_score_gemma":0.01008257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00299537,"about_ca_topic_score_gemma":0.01060583,"domain_scores_codex":[0.9873024,0.006941113,0.00106283,0.0007707805,0.003599127,0.0003238252],"domain_scores_gemma":[0.9676542,0.0209046,0.001337721,0.002968157,0.003513718,0.003621622],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001387181,0.0000669754,0.0001775759,0.0009196639,0.00002551037,0.0002951061,0.003330184,0.0006674077,0.0004445022,0.07026799,0.7863566,0.1374348],"study_design_scores_gemma":[0.000009891845,0.00001687445,0.0001054888,0.0005285551,0.000003439597,0.0003319679,0.0008406049,0.0004582673,0.00009517237,0.06187453,0.9357133,0.00002177052],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005708524,0.02716972,0.7012835,0.08691855,0.008276096,0.002892822,0.001903037,0.01264367,0.1583417],"genre_scores_gemma":[0.003457072,0.01328593,0.8777403,0.01311802,0.001348226,0.003608401,0.001257525,0.003423945,0.08276062],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9805208,"threshold_uncertainty_score":0.1555823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0220270537132456,"score_gpt":0.3122419050171739,"score_spread":0.2902148513039283,"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."}}