{"id":"W4380447143","doi":"10.1101/2023.06.05.543618","title":"Too many big promises: What is holding back cyanobacterial research and applications?","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Algal biology and biofuel production","field":"Energy","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Cyanobacteria; Set (abstract data type); Work (physics); Field (mathematics); Scale (ratio); Climate change; Environmental resource management; Data science; Business; Environmental planning; Environmental science; Political science; Computer science; Ecology; Engineering; Geography; Biology; Cartography","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.06623273,0.0006236278,0.0009651851,0.002108332,0.01542153,0.02782981,0.002912007,0.008698633,0.006823428],"category_scores_gemma":[0.07420994,0.0006191246,0.0007735007,0.004348706,0.01483584,0.03085793,0.008590613,0.01228151,0.001509143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01110746,"about_ca_system_score_gemma":0.02759074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007440466,"about_ca_topic_score_gemma":0.006634677,"domain_scores_codex":[0.9472896,0.02888338,0.001952831,0.00279991,0.01375672,0.005317554],"domain_scores_gemma":[0.8648143,0.08645682,0.007256482,0.003333898,0.02066633,0.01747219],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000344742,0.0003272264,0.01656475,0.006858332,0.0001075334,0.002849005,0.3643477,0.0004579443,0.01028274,0.1132263,0.1803517,0.3042821],"study_design_scores_gemma":[0.00001168063,0.0001346675,0.005110311,0.003370812,0.0000280023,0.0007637592,0.5369625,0.0002662334,0.001218167,0.02172795,0.4302915,0.0001143895],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.05873027,0.04531387,0.004037098,0.875079,0.004494134,0.00006428816,0.0001421719,0.0001125709,0.01202662],"genre_scores_gemma":[0.6759842,0.08243018,0.00926539,0.2173035,0.004614247,0.0002475613,0.0003124258,0.0004017703,0.009440807],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.06623273,"threshold_uncertainty_score":0.3502763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06214966940999064,"score_gpt":0.2825109643433265,"score_spread":0.2203612949333358,"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."}}