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Record W6942432759 · doi:10.14288/1.0363939

[In his own voice: recordings of a series of lectures by Dr. Vladimir J. Krajina on the Biogeoclimatic Zones of British Columbia, Lecture 2B]

2018· other· en· W6942432759 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Collections · 2018
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsWhite (mutation)Field tripPinus <genus>Field (mathematics)Sadness

Abstract

fetched live from OpenAlex

Lecture 2B: Dr. Krajina speaks on the main biogeoclimatic zones of the BC Interior, including the Cariboo Zone (name has since been changed), Interior Western Hemlock (IWH) and Interior Douglas fir (IDF) zones. The first 28 minutes are from the lecture before leaving on the weekend field trip to the BC interior. The lecture includes comments about the differences between the two ‘wet’ zones in BC (Coastal and Interior), and remarks on some of the main fungal pathogens that affect coniferous trees in BC (Indian paint fungus, white pine blister rust, Fomes (=Phellinus) pini). The second part continues after the field trip. There is a noticeable change in Krajina’s voice, possibly from a cold or tiredness from the long road trip. He talks about the species and ecological conditions seen on the field trip and comments on his own research showing effects of calcium deficiency on root development in conifers (especially, Pinus monticola). There is also a deepened sadness as he reminisces about the great losses of productive forest lands brought about by the construction of dams on the Columbia River.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.818
Threshold uncertainty score0.504

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.1510.060

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.242
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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